{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Factor Model of Portfolio Return (solution)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: numpy==1.14.5 in /opt/conda/lib/python3.6/site-packages (from -r requirements.txt (line 1))\n",
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      "Requirement already satisfied: jsonschema!=2.5.0,>=2.4 in /opt/conda/lib/python3.6/site-packages (from nbformat>=4.2->plotly==2.2.3->-r requirements.txt (line 3))\n",
      "Requirement already satisfied: traitlets>=4.1 in /opt/conda/lib/python3.6/site-packages (from nbformat>=4.2->plotly==2.2.3->-r requirements.txt (line 3))\n",
      "Requirement already satisfied: ipython-genutils in /opt/conda/lib/python3.6/site-packages (from nbformat>=4.2->plotly==2.2.3->-r requirements.txt (line 3))\n",
      "Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /opt/conda/lib/python3.6/site-packages (from requests->plotly==2.2.3->-r requirements.txt (line 3))\n",
      "Requirement already satisfied: idna<2.7,>=2.5 in /opt/conda/lib/python3.6/site-packages (from requests->plotly==2.2.3->-r requirements.txt (line 3))\n",
      "Requirement already satisfied: urllib3<1.23,>=1.21.1 in /opt/conda/lib/python3.6/site-packages (from requests->plotly==2.2.3->-r requirements.txt (line 3))\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.6/site-packages (from requests->plotly==2.2.3->-r requirements.txt (line 3))\n",
      "Requirement already satisfied: python-editor>=0.3 in /opt/conda/lib/python3.6/site-packages (from alembic>=0.7.7->zipline===1.2.0->-r requirements.txt (line 6))\n",
      "Requirement already satisfied: requests-ftp in /opt/conda/lib/python3.6/site-packages (from pandas-datareader<0.6,>=0.2.1->zipline===1.2.0->-r requirements.txt (line 6))\n",
      "\u001b[33mYou are using pip version 9.0.1, however version 18.1 is available.\n",
      "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "!{sys.executable} -m pip install -r requirements.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import time\n",
    "import os\n",
    "import quiz_helper\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "plt.style.use('ggplot')\n",
    "plt.rcParams['figure.figsize'] = (14, 8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### data bundle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import quiz_helper\n",
    "from zipline.data import bundles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data Registered\n"
     ]
    }
   ],
   "source": [
    "os.environ['ZIPLINE_ROOT'] = os.path.join(os.getcwd(), '..', '..','data','module_4_quizzes_eod')\n",
    "ingest_func = bundles.csvdir.csvdir_equities(['daily'], quiz_helper.EOD_BUNDLE_NAME)\n",
    "bundles.register(quiz_helper.EOD_BUNDLE_NAME, ingest_func)\n",
    "print('Data Registered')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Build pipeline engine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from zipline.pipeline import Pipeline\n",
    "from zipline.pipeline.factors import AverageDollarVolume\n",
    "from zipline.utils.calendars import get_calendar\n",
    "\n",
    "universe = AverageDollarVolume(window_length=120).top(500) \n",
    "trading_calendar = get_calendar('NYSE') \n",
    "bundle_data = bundles.load(quiz_helper.EOD_BUNDLE_NAME)\n",
    "engine = quiz_helper.build_pipeline_engine(bundle_data, trading_calendar)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View Data¶\n",
    "With the pipeline engine built, let's get the stocks at the end of the period in the universe we're using. We'll use these tickers to generate the returns data for the our risk model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Equity(0 [A]),\n",
       " Equity(1 [AAL]),\n",
       " Equity(2 [AAP]),\n",
       " Equity(3 [AAPL]),\n",
       " Equity(4 [ABBV]),\n",
       " Equity(5 [ABC]),\n",
       " Equity(6 [ABT]),\n",
       " Equity(7 [ACN]),\n",
       " Equity(8 [ADBE]),\n",
       " Equity(9 [ADI]),\n",
       " Equity(10 [ADM]),\n",
       " Equity(11 [ADP]),\n",
       " Equity(12 [ADS]),\n",
       " Equity(13 [ADSK]),\n",
       " Equity(14 [AEE]),\n",
       " Equity(15 [AEP]),\n",
       " Equity(16 [AES]),\n",
       " Equity(17 [AET]),\n",
       " Equity(18 [AFL]),\n",
       " Equity(19 [AGN]),\n",
       " Equity(20 [AIG]),\n",
       " Equity(21 [AIV]),\n",
       " Equity(22 [AIZ]),\n",
       " Equity(23 [AJG]),\n",
       " Equity(24 [AKAM]),\n",
       " Equity(25 [ALB]),\n",
       " Equity(26 [ALGN]),\n",
       " Equity(27 [ALK]),\n",
       " Equity(28 [ALL]),\n",
       " Equity(29 [ALLE]),\n",
       " Equity(30 [ALXN]),\n",
       " Equity(31 [AMAT]),\n",
       " Equity(32 [AMD]),\n",
       " Equity(33 [AME]),\n",
       " Equity(34 [AMG]),\n",
       " Equity(35 [AMGN]),\n",
       " Equity(36 [AMP]),\n",
       " Equity(37 [AMT]),\n",
       " Equity(38 [AMZN]),\n",
       " Equity(39 [ANDV]),\n",
       " Equity(40 [ANSS]),\n",
       " Equity(41 [ANTM]),\n",
       " Equity(42 [AON]),\n",
       " Equity(43 [AOS]),\n",
       " Equity(44 [APA]),\n",
       " Equity(45 [APC]),\n",
       " Equity(46 [APD]),\n",
       " Equity(47 [APH]),\n",
       " Equity(48 [ARE]),\n",
       " Equity(49 [ARNC]),\n",
       " Equity(50 [ATVI]),\n",
       " Equity(51 [AVB]),\n",
       " Equity(52 [AVGO]),\n",
       " Equity(53 [AVY]),\n",
       " Equity(54 [AWK]),\n",
       " Equity(55 [AXP]),\n",
       " Equity(56 [AYI]),\n",
       " Equity(57 [AZO]),\n",
       " Equity(58 [BA]),\n",
       " Equity(59 [BAC]),\n",
       " Equity(60 [BAX]),\n",
       " Equity(61 [BBT]),\n",
       " Equity(62 [BBY]),\n",
       " Equity(63 [BCR]),\n",
       " Equity(64 [BDX]),\n",
       " Equity(65 [BEN]),\n",
       " Equity(66 [BIIB]),\n",
       " Equity(67 [BK]),\n",
       " Equity(68 [BLK]),\n",
       " Equity(69 [BLL]),\n",
       " Equity(70 [BMY]),\n",
       " Equity(71 [BSX]),\n",
       " Equity(72 [BWA]),\n",
       " Equity(73 [BXP]),\n",
       " Equity(74 [C]),\n",
       " Equity(75 [CA]),\n",
       " Equity(76 [CAG]),\n",
       " Equity(77 [CAH]),\n",
       " Equity(78 [CAT]),\n",
       " Equity(79 [CB]),\n",
       " Equity(80 [CBG]),\n",
       " Equity(81 [CBOE]),\n",
       " Equity(82 [CBS]),\n",
       " Equity(83 [CCI]),\n",
       " Equity(84 [CCL]),\n",
       " Equity(85 [CELG]),\n",
       " Equity(86 [CERN]),\n",
       " Equity(87 [CF]),\n",
       " Equity(88 [CFG]),\n",
       " Equity(89 [CHD]),\n",
       " Equity(90 [CHK]),\n",
       " Equity(91 [CHRW]),\n",
       " Equity(92 [CHTR]),\n",
       " Equity(93 [CI]),\n",
       " Equity(94 [CINF]),\n",
       " Equity(95 [CL]),\n",
       " Equity(96 [CLX]),\n",
       " Equity(97 [CMA]),\n",
       " Equity(98 [CMCSA]),\n",
       " Equity(99 [CME]),\n",
       " Equity(100 [CMG]),\n",
       " Equity(101 [CMI]),\n",
       " Equity(102 [CMS]),\n",
       " Equity(103 [CNC]),\n",
       " Equity(104 [CNP]),\n",
       " Equity(105 [COF]),\n",
       " Equity(106 [COG]),\n",
       " Equity(107 [COL]),\n",
       " Equity(108 [COO]),\n",
       " Equity(109 [COP]),\n",
       " Equity(110 [COST]),\n",
       " Equity(111 [COTY]),\n",
       " Equity(112 [CPB]),\n",
       " Equity(113 [CRM]),\n",
       " Equity(114 [CSCO]),\n",
       " Equity(115 [CSRA]),\n",
       " Equity(116 [CSX]),\n",
       " Equity(117 [CTAS]),\n",
       " Equity(118 [CTL]),\n",
       " Equity(119 [CTSH]),\n",
       " Equity(120 [CTXS]),\n",
       " Equity(121 [CVS]),\n",
       " Equity(122 [CVX]),\n",
       " Equity(123 [CXO]),\n",
       " Equity(124 [D]),\n",
       " Equity(125 [DAL]),\n",
       " Equity(126 [DE]),\n",
       " Equity(127 [DFS]),\n",
       " Equity(128 [DG]),\n",
       " Equity(129 [DGX]),\n",
       " Equity(130 [DHI]),\n",
       " Equity(131 [DHR]),\n",
       " Equity(132 [DIS]),\n",
       " Equity(133 [DISCA]),\n",
       " Equity(134 [DISCK]),\n",
       " Equity(135 [DISH]),\n",
       " Equity(136 [DLR]),\n",
       " Equity(137 [DLTR]),\n",
       " Equity(138 [DOV]),\n",
       " Equity(139 [DPS]),\n",
       " Equity(140 [DRE]),\n",
       " Equity(141 [DRI]),\n",
       " Equity(142 [DTE]),\n",
       " Equity(143 [DUK]),\n",
       " Equity(144 [DVA]),\n",
       " Equity(145 [DVN]),\n",
       " Equity(146 [EA]),\n",
       " Equity(147 [EBAY]),\n",
       " Equity(148 [ECL]),\n",
       " Equity(149 [ED]),\n",
       " Equity(150 [EFX]),\n",
       " Equity(151 [EIX]),\n",
       " Equity(152 [EL]),\n",
       " Equity(153 [EMN]),\n",
       " Equity(154 [EMR]),\n",
       " Equity(155 [EOG]),\n",
       " Equity(156 [EQIX]),\n",
       " Equity(157 [EQR]),\n",
       " Equity(158 [EQT]),\n",
       " Equity(159 [ES]),\n",
       " Equity(160 [ESRX]),\n",
       " Equity(161 [ESS]),\n",
       " Equity(162 [ETFC]),\n",
       " Equity(163 [ETN]),\n",
       " Equity(164 [ETR]),\n",
       " Equity(165 [EVHC]),\n",
       " Equity(166 [EW]),\n",
       " Equity(167 [EXC]),\n",
       " Equity(168 [EXPD]),\n",
       " Equity(169 [EXPE]),\n",
       " Equity(170 [EXR]),\n",
       " Equity(171 [F]),\n",
       " Equity(172 [FAST]),\n",
       " Equity(173 [FB]),\n",
       " Equity(174 [FBHS]),\n",
       " Equity(175 [FCX]),\n",
       " Equity(176 [FDX]),\n",
       " Equity(177 [FE]),\n",
       " Equity(178 [FFIV]),\n",
       " Equity(179 [FIS]),\n",
       " Equity(180 [FISV]),\n",
       " Equity(181 [FITB]),\n",
       " Equity(182 [FL]),\n",
       " Equity(183 [FLIR]),\n",
       " Equity(184 [FLR]),\n",
       " Equity(185 [FLS]),\n",
       " Equity(186 [FMC]),\n",
       " Equity(187 [FOX]),\n",
       " Equity(188 [FOXA]),\n",
       " Equity(189 [FRT]),\n",
       " Equity(190 [FTI]),\n",
       " Equity(191 [GD]),\n",
       " Equity(192 [GE]),\n",
       " Equity(193 [GGP]),\n",
       " Equity(194 [GILD]),\n",
       " Equity(195 [GIS]),\n",
       " Equity(196 [GLW]),\n",
       " Equity(197 [GM]),\n",
       " Equity(198 [GOOG]),\n",
       " Equity(199 [GOOGL]),\n",
       " Equity(200 [GPC]),\n",
       " Equity(201 [GPN]),\n",
       " Equity(202 [GPS]),\n",
       " Equity(203 [GRMN]),\n",
       " Equity(204 [GS]),\n",
       " Equity(205 [GT]),\n",
       " Equity(206 [GWW]),\n",
       " Equity(207 [HAL]),\n",
       " Equity(208 [HAS]),\n",
       " Equity(209 [HBAN]),\n",
       " Equity(210 [HBI]),\n",
       " Equity(211 [HCA]),\n",
       " Equity(212 [HCN]),\n",
       " Equity(213 [HCP]),\n",
       " Equity(214 [HD]),\n",
       " Equity(215 [HES]),\n",
       " Equity(216 [HIG]),\n",
       " Equity(217 [HLT]),\n",
       " Equity(218 [HOG]),\n",
       " Equity(219 [HOLX]),\n",
       " Equity(220 [HON]),\n",
       " Equity(221 [HP]),\n",
       " Equity(222 [HPE]),\n",
       " Equity(223 [HPQ]),\n",
       " Equity(224 [HRB]),\n",
       " Equity(225 [HRL]),\n",
       " Equity(226 [HRS]),\n",
       " Equity(227 [HSIC]),\n",
       " Equity(228 [HST]),\n",
       " Equity(229 [HSY]),\n",
       " Equity(230 [HUM]),\n",
       " Equity(231 [IBM]),\n",
       " Equity(232 [ICE]),\n",
       " Equity(233 [IDXX]),\n",
       " Equity(234 [IFF]),\n",
       " Equity(235 [ILMN]),\n",
       " Equity(236 [INCY]),\n",
       " Equity(237 [INFO]),\n",
       " Equity(238 [INTC]),\n",
       " Equity(239 [INTU]),\n",
       " Equity(240 [IP]),\n",
       " Equity(241 [IPG]),\n",
       " Equity(242 [IR]),\n",
       " Equity(243 [IRM]),\n",
       " Equity(244 [ISRG]),\n",
       " Equity(245 [IT]),\n",
       " Equity(246 [ITW]),\n",
       " Equity(247 [IVZ]),\n",
       " Equity(248 [JBHT]),\n",
       " Equity(249 [JCI]),\n",
       " Equity(250 [JEC]),\n",
       " Equity(251 [JNJ]),\n",
       " Equity(252 [JNPR]),\n",
       " Equity(253 [JPM]),\n",
       " Equity(254 [JWN]),\n",
       " Equity(255 [K]),\n",
       " Equity(256 [KEY]),\n",
       " Equity(257 [KHC]),\n",
       " Equity(258 [KIM]),\n",
       " Equity(259 [KLAC]),\n",
       " Equity(260 [KMB]),\n",
       " Equity(261 [KMI]),\n",
       " Equity(262 [KMX]),\n",
       " Equity(263 [KO]),\n",
       " Equity(264 [KORS]),\n",
       " Equity(265 [KR]),\n",
       " Equity(266 [KSS]),\n",
       " Equity(267 [KSU]),\n",
       " Equity(268 [L]),\n",
       " Equity(269 [LB]),\n",
       " Equity(270 [LEG]),\n",
       " Equity(271 [LEN]),\n",
       " Equity(272 [LH]),\n",
       " Equity(273 [LKQ]),\n",
       " Equity(274 [LLL]),\n",
       " Equity(275 [LLY]),\n",
       " Equity(276 [LMT]),\n",
       " Equity(277 [LNC]),\n",
       " Equity(278 [LNT]),\n",
       " Equity(279 [LOW]),\n",
       " Equity(280 [LRCX]),\n",
       " Equity(281 [LUK]),\n",
       " Equity(282 [LUV]),\n",
       " Equity(283 [LVLT]),\n",
       " Equity(284 [LYB]),\n",
       " Equity(285 [M]),\n",
       " Equity(286 [MA]),\n",
       " Equity(287 [MAA]),\n",
       " Equity(288 [MAC]),\n",
       " Equity(289 [MAR]),\n",
       " Equity(290 [MAS]),\n",
       " Equity(291 [MAT]),\n",
       " Equity(292 [MCD]),\n",
       " Equity(293 [MCHP]),\n",
       " Equity(294 [MCK]),\n",
       " Equity(295 [MCO]),\n",
       " Equity(296 [MDLZ]),\n",
       " Equity(297 [MDT]),\n",
       " Equity(298 [MET]),\n",
       " Equity(299 [MGM]),\n",
       " Equity(300 [MHK]),\n",
       " Equity(301 [MKC]),\n",
       " Equity(302 [MLM]),\n",
       " Equity(303 [MMC]),\n",
       " Equity(304 [MNST]),\n",
       " Equity(305 [MO]),\n",
       " Equity(306 [MON]),\n",
       " Equity(307 [MOS]),\n",
       " Equity(308 [MPC]),\n",
       " Equity(309 [MRK]),\n",
       " Equity(310 [MRO]),\n",
       " Equity(311 [MS]),\n",
       " Equity(312 [MSFT]),\n",
       " Equity(313 [MSI]),\n",
       " Equity(314 [MTB]),\n",
       " Equity(315 [MTD]),\n",
       " Equity(316 [MU]),\n",
       " Equity(317 [MYL]),\n",
       " Equity(318 [NAVI]),\n",
       " Equity(319 [NBL]),\n",
       " Equity(320 [NDAQ]),\n",
       " Equity(321 [NEE]),\n",
       " Equity(322 [NEM]),\n",
       " Equity(323 [NFLX]),\n",
       " Equity(324 [NFX]),\n",
       " Equity(325 [NI]),\n",
       " Equity(326 [NKE]),\n",
       " Equity(327 [NLSN]),\n",
       " Equity(328 [NOC]),\n",
       " Equity(329 [NOV]),\n",
       " Equity(330 [NRG]),\n",
       " Equity(331 [NSC]),\n",
       " Equity(332 [NTAP]),\n",
       " Equity(333 [NTRS]),\n",
       " Equity(334 [NUE]),\n",
       " Equity(335 [NVDA]),\n",
       " Equity(336 [NWL]),\n",
       " Equity(337 [NWS]),\n",
       " Equity(338 [NWSA]),\n",
       " Equity(339 [O]),\n",
       " Equity(340 [OKE]),\n",
       " Equity(341 [OMC]),\n",
       " Equity(342 [ORCL]),\n",
       " Equity(343 [ORLY]),\n",
       " Equity(344 [OXY]),\n",
       " Equity(345 [PAYX]),\n",
       " Equity(346 [PBCT]),\n",
       " Equity(347 [PCAR]),\n",
       " Equity(348 [PCG]),\n",
       " Equity(349 [PDCO]),\n",
       " Equity(350 [PEG]),\n",
       " Equity(351 [PEP]),\n",
       " Equity(352 [PFE]),\n",
       " Equity(353 [PFG]),\n",
       " Equity(354 [PG]),\n",
       " Equity(355 [PGR]),\n",
       " Equity(356 [PH]),\n",
       " Equity(357 [PHM]),\n",
       " Equity(358 [PKG]),\n",
       " Equity(359 [PKI]),\n",
       " Equity(360 [PLD]),\n",
       " Equity(361 [PM]),\n",
       " Equity(362 [PNC]),\n",
       " Equity(363 [PNR]),\n",
       " Equity(364 [PNW]),\n",
       " Equity(365 [PPG]),\n",
       " Equity(366 [PPL]),\n",
       " Equity(367 [PRGO]),\n",
       " Equity(368 [PRU]),\n",
       " Equity(369 [PSA]),\n",
       " Equity(370 [PSX]),\n",
       " Equity(371 [PVH]),\n",
       " Equity(372 [PWR]),\n",
       " Equity(373 [PX]),\n",
       " Equity(374 [PXD]),\n",
       " Equity(375 [PYPL]),\n",
       " Equity(376 [QCOM]),\n",
       " Equity(377 [QRVO]),\n",
       " Equity(378 [RCL]),\n",
       " Equity(379 [RE]),\n",
       " Equity(380 [REG]),\n",
       " Equity(381 [REGN]),\n",
       " Equity(382 [RF]),\n",
       " Equity(383 [RHI]),\n",
       " Equity(384 [RHT]),\n",
       " Equity(385 [RJF]),\n",
       " Equity(386 [RL]),\n",
       " Equity(387 [RMD]),\n",
       " Equity(388 [ROK]),\n",
       " Equity(389 [ROP]),\n",
       " Equity(390 [ROST]),\n",
       " Equity(391 [RRC]),\n",
       " Equity(392 [RSG]),\n",
       " Equity(393 [RTN]),\n",
       " Equity(394 [SBAC]),\n",
       " Equity(395 [SBUX]),\n",
       " Equity(396 [SCG]),\n",
       " Equity(397 [SCHW]),\n",
       " Equity(398 [SEE]),\n",
       " Equity(399 [SHW]),\n",
       " Equity(400 [SIG]),\n",
       " Equity(401 [SJM]),\n",
       " Equity(402 [SLB]),\n",
       " Equity(403 [SLG]),\n",
       " Equity(404 [SNA]),\n",
       " Equity(405 [SNI]),\n",
       " Equity(406 [SNPS]),\n",
       " Equity(407 [SO]),\n",
       " Equity(408 [SPG]),\n",
       " Equity(409 [SPLS]),\n",
       " Equity(410 [SRCL]),\n",
       " Equity(411 [SRE]),\n",
       " Equity(412 [STI]),\n",
       " Equity(413 [STT]),\n",
       " Equity(414 [STX]),\n",
       " Equity(415 [STZ]),\n",
       " Equity(416 [SWK]),\n",
       " Equity(417 [SWKS]),\n",
       " Equity(418 [SYF]),\n",
       " Equity(419 [SYK]),\n",
       " Equity(420 [SYMC]),\n",
       " Equity(421 [SYY]),\n",
       " Equity(422 [T]),\n",
       " Equity(423 [TAP]),\n",
       " Equity(424 [TDG]),\n",
       " Equity(425 [TEL]),\n",
       " Equity(426 [TGT]),\n",
       " Equity(427 [TIF]),\n",
       " Equity(428 [TJX]),\n",
       " Equity(429 [TMK]),\n",
       " Equity(430 [TMO]),\n",
       " Equity(431 [TRIP]),\n",
       " Equity(432 [TROW]),\n",
       " Equity(433 [TRV]),\n",
       " Equity(434 [TSCO]),\n",
       " Equity(435 [TSN]),\n",
       " Equity(436 [TSS]),\n",
       " Equity(437 [TWX]),\n",
       " Equity(438 [TXN]),\n",
       " Equity(439 [TXT]),\n",
       " Equity(440 [UAA]),\n",
       " Equity(441 [UAL]),\n",
       " Equity(442 [UDR]),\n",
       " Equity(443 [UHS]),\n",
       " Equity(444 [ULTA]),\n",
       " Equity(445 [UNH]),\n",
       " Equity(446 [UNM]),\n",
       " Equity(447 [UNP]),\n",
       " Equity(448 [UPS]),\n",
       " Equity(449 [URI]),\n",
       " Equity(450 [USB]),\n",
       " Equity(451 [UTX]),\n",
       " Equity(452 [V]),\n",
       " Equity(453 [VAR]),\n",
       " Equity(454 [VFC]),\n",
       " Equity(455 [VIAB]),\n",
       " Equity(456 [VLO]),\n",
       " Equity(457 [VMC]),\n",
       " Equity(458 [VNO]),\n",
       " Equity(459 [VRSK]),\n",
       " Equity(460 [VRSN]),\n",
       " Equity(461 [VRTX]),\n",
       " Equity(462 [VTR]),\n",
       " Equity(463 [VZ]),\n",
       " Equity(464 [WAT]),\n",
       " Equity(465 [WBA]),\n",
       " Equity(466 [WDC]),\n",
       " Equity(467 [WEC]),\n",
       " Equity(468 [WFC]),\n",
       " Equity(469 [WHR]),\n",
       " Equity(471 [WM]),\n",
       " Equity(472 [WMB]),\n",
       " Equity(473 [WMT]),\n",
       " Equity(474 [WRK]),\n",
       " Equity(475 [WU]),\n",
       " Equity(476 [WY]),\n",
       " Equity(477 [WYN]),\n",
       " Equity(478 [WYNN]),\n",
       " Equity(479 [XEC]),\n",
       " Equity(480 [XEL]),\n",
       " Equity(481 [XL]),\n",
       " Equity(482 [XLNX]),\n",
       " Equity(483 [XOM]),\n",
       " Equity(484 [XRAY]),\n",
       " Equity(485 [XRX]),\n",
       " Equity(486 [XYL]),\n",
       " Equity(487 [YUM]),\n",
       " Equity(488 [ZBH]),\n",
       " Equity(489 [ZION]),\n",
       " Equity(490 [ZTS])]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "universe_end_date = pd.Timestamp('2016-01-05', tz='UTC')\n",
    "\n",
    "universe_tickers = engine\\\n",
    "    .run_pipeline(\n",
    "        Pipeline(screen=universe),\n",
    "        universe_end_date,\n",
    "        universe_end_date)\\\n",
    "    .index.get_level_values(1)\\\n",
    "    .values.tolist()\n",
    "    \n",
    "universe_tickers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "490"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(universe_tickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from zipline.data.data_portal import DataPortal\n",
    "\n",
    "data_portal = DataPortal(\n",
    "    bundle_data.asset_finder,\n",
    "    trading_calendar=trading_calendar,\n",
    "    first_trading_day=bundle_data.equity_daily_bar_reader.first_trading_day,\n",
    "    equity_minute_reader=None,\n",
    "    equity_daily_reader=bundle_data.equity_daily_bar_reader,\n",
    "    adjustment_reader=bundle_data.adjustment_reader)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get pricing data helper function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from quiz_helper import get_pricing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## get pricing data into a dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Equity(0 [A])</th>\n",
       "      <th>Equity(1 [AAL])</th>\n",
       "      <th>Equity(2 [AAP])</th>\n",
       "      <th>Equity(3 [AAPL])</th>\n",
       "      <th>Equity(4 [ABBV])</th>\n",
       "      <th>Equity(5 [ABC])</th>\n",
       "      <th>Equity(6 [ABT])</th>\n",
       "      <th>Equity(7 [ACN])</th>\n",
       "      <th>Equity(8 [ADBE])</th>\n",
       "      <th>Equity(9 [ADI])</th>\n",
       "      <th>...</th>\n",
       "      <th>Equity(481 [XL])</th>\n",
       "      <th>Equity(482 [XLNX])</th>\n",
       "      <th>Equity(483 [XOM])</th>\n",
       "      <th>Equity(484 [XRAY])</th>\n",
       "      <th>Equity(485 [XRX])</th>\n",
       "      <th>Equity(486 [XYL])</th>\n",
       "      <th>Equity(487 [YUM])</th>\n",
       "      <th>Equity(488 [ZBH])</th>\n",
       "      <th>Equity(489 [ZION])</th>\n",
       "      <th>Equity(490 [ZTS])</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-07 00:00:00+00:00</th>\n",
       "      <td>0.008437</td>\n",
       "      <td>0.014230</td>\n",
       "      <td>0.026702</td>\n",
       "      <td>0.007146</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001994</td>\n",
       "      <td>0.004165</td>\n",
       "      <td>0.001648</td>\n",
       "      <td>-0.007127</td>\n",
       "      <td>-0.005818</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.001838</td>\n",
       "      <td>-0.005619</td>\n",
       "      <td>0.005461</td>\n",
       "      <td>-0.004044</td>\n",
       "      <td>-0.013953</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.012457</td>\n",
       "      <td>-0.000181</td>\n",
       "      <td>-0.010458</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-10 00:00:00+00:00</th>\n",
       "      <td>-0.004174</td>\n",
       "      <td>0.006195</td>\n",
       "      <td>0.007435</td>\n",
       "      <td>0.018852</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.005714</td>\n",
       "      <td>-0.008896</td>\n",
       "      <td>-0.008854</td>\n",
       "      <td>0.028714</td>\n",
       "      <td>0.002926</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000947</td>\n",
       "      <td>0.007814</td>\n",
       "      <td>-0.006081</td>\n",
       "      <td>0.010466</td>\n",
       "      <td>0.009733</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001440</td>\n",
       "      <td>0.007784</td>\n",
       "      <td>-0.017945</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-11 00:00:00+00:00</th>\n",
       "      <td>-0.001886</td>\n",
       "      <td>-0.043644</td>\n",
       "      <td>-0.005927</td>\n",
       "      <td>-0.002367</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009783</td>\n",
       "      <td>-0.002067</td>\n",
       "      <td>0.013717</td>\n",
       "      <td>0.000607</td>\n",
       "      <td>0.008753</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001314</td>\n",
       "      <td>0.010179</td>\n",
       "      <td>0.007442</td>\n",
       "      <td>0.007351</td>\n",
       "      <td>0.006116</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.006470</td>\n",
       "      <td>0.035676</td>\n",
       "      <td>0.007467</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-12 00:00:00+00:00</th>\n",
       "      <td>0.017254</td>\n",
       "      <td>-0.008237</td>\n",
       "      <td>0.013387</td>\n",
       "      <td>0.008133</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.005979</td>\n",
       "      <td>-0.001011</td>\n",
       "      <td>0.022969</td>\n",
       "      <td>0.017950</td>\n",
       "      <td>0.000257</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004986</td>\n",
       "      <td>0.015666</td>\n",
       "      <td>0.011763</td>\n",
       "      <td>0.027182</td>\n",
       "      <td>0.004386</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002631</td>\n",
       "      <td>0.014741</td>\n",
       "      <td>-0.011903</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-13 00:00:00+00:00</th>\n",
       "      <td>-0.004559</td>\n",
       "      <td>0.000955</td>\n",
       "      <td>0.003031</td>\n",
       "      <td>0.003657</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.014925</td>\n",
       "      <td>-0.004451</td>\n",
       "      <td>-0.000400</td>\n",
       "      <td>-0.005719</td>\n",
       "      <td>-0.005012</td>\n",
       "      <td>...</td>\n",
       "      <td>0.030499</td>\n",
       "      <td>-0.003217</td>\n",
       "      <td>0.001694</td>\n",
       "      <td>0.000547</td>\n",
       "      <td>-0.018235</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.005084</td>\n",
       "      <td>-0.004665</td>\n",
       "      <td>-0.009178</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-14 00:00:00+00:00</th>\n",
       "      <td>0.003439</td>\n",
       "      <td>-0.009156</td>\n",
       "      <td>0.003022</td>\n",
       "      <td>0.008106</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001395</td>\n",
       "      <td>-0.010111</td>\n",
       "      <td>0.002590</td>\n",
       "      <td>0.012283</td>\n",
       "      <td>0.019827</td>\n",
       "      <td>...</td>\n",
       "      <td>0.026607</td>\n",
       "      <td>0.025894</td>\n",
       "      <td>0.014743</td>\n",
       "      <td>-0.000287</td>\n",
       "      <td>0.026494</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.021661</td>\n",
       "      <td>0.005949</td>\n",
       "      <td>0.033177</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-18 00:00:00+00:00</th>\n",
       "      <td>0.034254</td>\n",
       "      <td>-0.062085</td>\n",
       "      <td>-0.004286</td>\n",
       "      <td>-0.022474</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020889</td>\n",
       "      <td>0.006621</td>\n",
       "      <td>0.006998</td>\n",
       "      <td>0.011542</td>\n",
       "      <td>0.032645</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001678</td>\n",
       "      <td>0.002501</td>\n",
       "      <td>0.011163</td>\n",
       "      <td>0.011589</td>\n",
       "      <td>0.006044</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.029453</td>\n",
       "      <td>0.006998</td>\n",
       "      <td>-0.008534</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-19 00:00:00+00:00</th>\n",
       "      <td>-0.010224</td>\n",
       "      <td>-0.008929</td>\n",
       "      <td>0.008754</td>\n",
       "      <td>-0.005314</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.017144</td>\n",
       "      <td>0.002753</td>\n",
       "      <td>-0.002962</td>\n",
       "      <td>-0.007899</td>\n",
       "      <td>-0.020575</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.014834</td>\n",
       "      <td>-0.023590</td>\n",
       "      <td>-0.005968</td>\n",
       "      <td>-0.019899</td>\n",
       "      <td>-0.012847</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000818</td>\n",
       "      <td>-0.004098</td>\n",
       "      <td>-0.018433</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-20 00:00:00+00:00</th>\n",
       "      <td>-0.008496</td>\n",
       "      <td>0.021953</td>\n",
       "      <td>-0.004732</td>\n",
       "      <td>-0.018189</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004794</td>\n",
       "      <td>0.013322</td>\n",
       "      <td>0.018713</td>\n",
       "      <td>-0.012386</td>\n",
       "      <td>-0.002818</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.024512</td>\n",
       "      <td>0.007744</td>\n",
       "      <td>-0.006261</td>\n",
       "      <td>-0.000841</td>\n",
       "      <td>-0.033798</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.013182</td>\n",
       "      <td>-0.001612</td>\n",
       "      <td>-0.007972</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-21 00:00:00+00:00</th>\n",
       "      <td>0.007873</td>\n",
       "      <td>-0.041038</td>\n",
       "      <td>0.005544</td>\n",
       "      <td>-0.017911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010642</td>\n",
       "      <td>-0.000853</td>\n",
       "      <td>-0.001952</td>\n",
       "      <td>-0.006569</td>\n",
       "      <td>-0.004113</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000615</td>\n",
       "      <td>0.015825</td>\n",
       "      <td>-0.003048</td>\n",
       "      <td>-0.000872</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.007590</td>\n",
       "      <td>0.009325</td>\n",
       "      <td>0.024020</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-24 00:00:00+00:00</th>\n",
       "      <td>0.014646</td>\n",
       "      <td>0.027473</td>\n",
       "      <td>-0.001106</td>\n",
       "      <td>0.032837</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005249</td>\n",
       "      <td>0.005223</td>\n",
       "      <td>0.008420</td>\n",
       "      <td>0.022843</td>\n",
       "      <td>0.014974</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012359</td>\n",
       "      <td>0.016011</td>\n",
       "      <td>-0.004943</td>\n",
       "      <td>0.001660</td>\n",
       "      <td>0.008049</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000601</td>\n",
       "      <td>-0.016501</td>\n",
       "      <td>-0.023021</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-25 00:00:00+00:00</th>\n",
       "      <td>-0.006736</td>\n",
       "      <td>0.002982</td>\n",
       "      <td>0.009146</td>\n",
       "      <td>0.011710</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.009363</td>\n",
       "      <td>-0.004347</td>\n",
       "      <td>0.004859</td>\n",
       "      <td>-0.013811</td>\n",
       "      <td>-0.014505</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002178</td>\n",
       "      <td>0.006273</td>\n",
       "      <td>0.001154</td>\n",
       "      <td>0.001134</td>\n",
       "      <td>0.015143</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.006208</td>\n",
       "      <td>0.017142</td>\n",
       "      <td>-0.008836</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-26 00:00:00+00:00</th>\n",
       "      <td>-0.030736</td>\n",
       "      <td>0.066133</td>\n",
       "      <td>0.003593</td>\n",
       "      <td>0.007193</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.012227</td>\n",
       "      <td>-0.025241</td>\n",
       "      <td>0.012192</td>\n",
       "      <td>-0.001192</td>\n",
       "      <td>0.002837</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002628</td>\n",
       "      <td>0.005934</td>\n",
       "      <td>0.012453</td>\n",
       "      <td>0.000552</td>\n",
       "      <td>-0.076291</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.004803</td>\n",
       "      <td>-0.019524</td>\n",
       "      <td>-0.010626</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-27 00:00:00+00:00</th>\n",
       "      <td>0.007721</td>\n",
       "      <td>0.023178</td>\n",
       "      <td>-0.001553</td>\n",
       "      <td>-0.001877</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.011833</td>\n",
       "      <td>-0.007928</td>\n",
       "      <td>0.000179</td>\n",
       "      <td>0.009845</td>\n",
       "      <td>0.007480</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014267</td>\n",
       "      <td>0.021169</td>\n",
       "      <td>0.002751</td>\n",
       "      <td>0.016396</td>\n",
       "      <td>0.024664</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.003746</td>\n",
       "      <td>0.068754</td>\n",
       "      <td>0.020160</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-28 00:00:00+00:00</th>\n",
       "      <td>-0.018846</td>\n",
       "      <td>-0.080553</td>\n",
       "      <td>-0.000936</td>\n",
       "      <td>-0.020710</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.022262</td>\n",
       "      <td>-0.019200</td>\n",
       "      <td>-0.016035</td>\n",
       "      <td>-0.040177</td>\n",
       "      <td>-0.022460</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.025647</td>\n",
       "      <td>-0.020108</td>\n",
       "      <td>-0.011131</td>\n",
       "      <td>-0.021871</td>\n",
       "      <td>-0.022229</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.025001</td>\n",
       "      <td>-0.008472</td>\n",
       "      <td>-0.013873</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-31 00:00:00+00:00</th>\n",
       "      <td>0.003608</td>\n",
       "      <td>-0.023615</td>\n",
       "      <td>-0.002351</td>\n",
       "      <td>0.009578</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.003893</td>\n",
       "      <td>-0.007248</td>\n",
       "      <td>-0.000980</td>\n",
       "      <td>0.017236</td>\n",
       "      <td>0.013818</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004846</td>\n",
       "      <td>0.000298</td>\n",
       "      <td>0.021396</td>\n",
       "      <td>-0.007560</td>\n",
       "      <td>0.006615</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.007748</td>\n",
       "      <td>0.009902</td>\n",
       "      <td>0.006378</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01 00:00:00+00:00</th>\n",
       "      <td>0.011654</td>\n",
       "      <td>-0.001047</td>\n",
       "      <td>-0.009218</td>\n",
       "      <td>0.016818</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.011976</td>\n",
       "      <td>0.001546</td>\n",
       "      <td>0.017498</td>\n",
       "      <td>0.013918</td>\n",
       "      <td>0.021624</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015687</td>\n",
       "      <td>0.032003</td>\n",
       "      <td>0.040037</td>\n",
       "      <td>0.024795</td>\n",
       "      <td>0.024498</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.014102</td>\n",
       "      <td>0.017746</td>\n",
       "      <td>0.030970</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-02 00:00:00+00:00</th>\n",
       "      <td>0.010112</td>\n",
       "      <td>-0.039304</td>\n",
       "      <td>-0.027477</td>\n",
       "      <td>-0.002053</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.021197</td>\n",
       "      <td>0.011068</td>\n",
       "      <td>0.003632</td>\n",
       "      <td>-0.002387</td>\n",
       "      <td>0.002280</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.012846</td>\n",
       "      <td>-0.004518</td>\n",
       "      <td>-0.005958</td>\n",
       "      <td>-0.010390</td>\n",
       "      <td>-0.001827</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006562</td>\n",
       "      <td>0.005161</td>\n",
       "      <td>-0.003706</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-03 00:00:00+00:00</th>\n",
       "      <td>-0.000289</td>\n",
       "      <td>0.007310</td>\n",
       "      <td>0.014126</td>\n",
       "      <td>-0.002560</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.003662</td>\n",
       "      <td>0.005894</td>\n",
       "      <td>0.004178</td>\n",
       "      <td>0.002991</td>\n",
       "      <td>-0.013341</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010430</td>\n",
       "      <td>-0.008169</td>\n",
       "      <td>0.000347</td>\n",
       "      <td>0.008556</td>\n",
       "      <td>0.004596</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.031413</td>\n",
       "      <td>-0.000333</td>\n",
       "      <td>-0.000394</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-04 00:00:00+00:00</th>\n",
       "      <td>0.005627</td>\n",
       "      <td>-0.036500</td>\n",
       "      <td>0.024014</td>\n",
       "      <td>0.008915</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.033047</td>\n",
       "      <td>0.002616</td>\n",
       "      <td>-0.004360</td>\n",
       "      <td>-0.005070</td>\n",
       "      <td>0.019659</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009471</td>\n",
       "      <td>0.024709</td>\n",
       "      <td>-0.001917</td>\n",
       "      <td>0.003048</td>\n",
       "      <td>-0.005506</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001408</td>\n",
       "      <td>0.002471</td>\n",
       "      <td>0.016111</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-07 00:00:00+00:00</th>\n",
       "      <td>0.007709</td>\n",
       "      <td>0.052046</td>\n",
       "      <td>0.008114</td>\n",
       "      <td>0.015538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.002178</td>\n",
       "      <td>-0.009341</td>\n",
       "      <td>0.002279</td>\n",
       "      <td>0.005995</td>\n",
       "      <td>-0.003514</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006801</td>\n",
       "      <td>-0.005073</td>\n",
       "      <td>0.007803</td>\n",
       "      <td>0.006852</td>\n",
       "      <td>0.002768</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002028</td>\n",
       "      <td>-0.010876</td>\n",
       "      <td>0.027617</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-08 00:00:00+00:00</th>\n",
       "      <td>0.010854</td>\n",
       "      <td>0.016455</td>\n",
       "      <td>0.006202</td>\n",
       "      <td>0.009440</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002182</td>\n",
       "      <td>-0.001738</td>\n",
       "      <td>-0.000557</td>\n",
       "      <td>0.000298</td>\n",
       "      <td>-0.006010</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003846</td>\n",
       "      <td>0.001795</td>\n",
       "      <td>-0.006077</td>\n",
       "      <td>0.005182</td>\n",
       "      <td>-0.002761</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003851</td>\n",
       "      <td>-0.000495</td>\n",
       "      <td>0.004780</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-09 00:00:00+00:00</th>\n",
       "      <td>0.004664</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.016955</td>\n",
       "      <td>0.008332</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003006</td>\n",
       "      <td>-0.001530</td>\n",
       "      <td>0.001138</td>\n",
       "      <td>-0.016682</td>\n",
       "      <td>0.004781</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.011837</td>\n",
       "      <td>-0.001792</td>\n",
       "      <td>-0.005178</td>\n",
       "      <td>-0.018441</td>\n",
       "      <td>0.003705</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.001821</td>\n",
       "      <td>-0.009851</td>\n",
       "      <td>-0.004757</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-10 00:00:00+00:00</th>\n",
       "      <td>0.000413</td>\n",
       "      <td>-0.003048</td>\n",
       "      <td>-0.011367</td>\n",
       "      <td>-0.010109</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001101</td>\n",
       "      <td>-0.001110</td>\n",
       "      <td>0.005503</td>\n",
       "      <td>0.016965</td>\n",
       "      <td>0.004513</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.008947</td>\n",
       "      <td>0.003914</td>\n",
       "      <td>0.007876</td>\n",
       "      <td>0.005512</td>\n",
       "      <td>-0.004624</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004853</td>\n",
       "      <td>0.011449</td>\n",
       "      <td>-0.026498</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-11 00:00:00+00:00</th>\n",
       "      <td>-0.007150</td>\n",
       "      <td>0.028364</td>\n",
       "      <td>0.000764</td>\n",
       "      <td>0.006505</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.001375</td>\n",
       "      <td>0.001534</td>\n",
       "      <td>-0.011146</td>\n",
       "      <td>0.002979</td>\n",
       "      <td>0.015007</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001705</td>\n",
       "      <td>0.010765</td>\n",
       "      <td>-0.004562</td>\n",
       "      <td>0.007147</td>\n",
       "      <td>0.012021</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000616</td>\n",
       "      <td>0.009660</td>\n",
       "      <td>0.014256</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-14 00:00:00+00:00</th>\n",
       "      <td>0.001663</td>\n",
       "      <td>-0.015790</td>\n",
       "      <td>-0.023274</td>\n",
       "      <td>0.006529</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005750</td>\n",
       "      <td>0.009245</td>\n",
       "      <td>0.000202</td>\n",
       "      <td>0.005643</td>\n",
       "      <td>0.009877</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.011616</td>\n",
       "      <td>0.000318</td>\n",
       "      <td>0.025230</td>\n",
       "      <td>-0.005443</td>\n",
       "      <td>0.005476</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010657</td>\n",
       "      <td>0.002484</td>\n",
       "      <td>-0.010021</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-15 00:00:00+00:00</th>\n",
       "      <td>-0.011905</td>\n",
       "      <td>0.011043</td>\n",
       "      <td>-0.003926</td>\n",
       "      <td>0.002016</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.007329</td>\n",
       "      <td>0.016750</td>\n",
       "      <td>-0.008021</td>\n",
       "      <td>0.002363</td>\n",
       "      <td>0.000239</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.006079</td>\n",
       "      <td>-0.001804</td>\n",
       "      <td>-0.022853</td>\n",
       "      <td>0.004097</td>\n",
       "      <td>0.003604</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008526</td>\n",
       "      <td>-0.001815</td>\n",
       "      <td>-0.004461</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-16 00:00:00+00:00</th>\n",
       "      <td>0.015123</td>\n",
       "      <td>0.001958</td>\n",
       "      <td>0.013860</td>\n",
       "      <td>0.008967</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.003554</td>\n",
       "      <td>-0.010502</td>\n",
       "      <td>0.027329</td>\n",
       "      <td>0.022098</td>\n",
       "      <td>-0.003905</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009174</td>\n",
       "      <td>0.003863</td>\n",
       "      <td>0.008682</td>\n",
       "      <td>0.000285</td>\n",
       "      <td>0.027093</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008898</td>\n",
       "      <td>0.010557</td>\n",
       "      <td>0.001206</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-17 00:00:00+00:00</th>\n",
       "      <td>-0.003311</td>\n",
       "      <td>-0.017791</td>\n",
       "      <td>-0.024844</td>\n",
       "      <td>-0.013309</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.029148</td>\n",
       "      <td>0.001301</td>\n",
       "      <td>0.011784</td>\n",
       "      <td>0.008360</td>\n",
       "      <td>0.008559</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015656</td>\n",
       "      <td>0.000318</td>\n",
       "      <td>0.002275</td>\n",
       "      <td>-0.001911</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003906</td>\n",
       "      <td>0.015325</td>\n",
       "      <td>-0.003227</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-18 00:00:00+00:00</th>\n",
       "      <td>0.011078</td>\n",
       "      <td>-0.020103</td>\n",
       "      <td>-0.006693</td>\n",
       "      <td>-0.021595</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009620</td>\n",
       "      <td>0.012106</td>\n",
       "      <td>-0.007953</td>\n",
       "      <td>0.011721</td>\n",
       "      <td>-0.001691</td>\n",
       "      <td>...</td>\n",
       "      <td>0.053404</td>\n",
       "      <td>0.001447</td>\n",
       "      <td>0.007393</td>\n",
       "      <td>0.013148</td>\n",
       "      <td>-0.004390</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.004110</td>\n",
       "      <td>0.023782</td>\n",
       "      <td>-0.017960</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-20 00:00:00+00:00</th>\n",
       "      <td>0.001072</td>\n",
       "      <td>-0.002373</td>\n",
       "      <td>0.002767</td>\n",
       "      <td>0.004381</td>\n",
       "      <td>0.009256</td>\n",
       "      <td>-0.000905</td>\n",
       "      <td>0.006113</td>\n",
       "      <td>0.006430</td>\n",
       "      <td>0.000545</td>\n",
       "      <td>-0.005843</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008131</td>\n",
       "      <td>0.000412</td>\n",
       "      <td>-0.006352</td>\n",
       "      <td>0.002793</td>\n",
       "      <td>0.002899</td>\n",
       "      <td>-0.004498</td>\n",
       "      <td>0.015060</td>\n",
       "      <td>-0.003176</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-23 00:00:00+00:00</th>\n",
       "      <td>-0.007094</td>\n",
       "      <td>0.002379</td>\n",
       "      <td>-0.001228</td>\n",
       "      <td>-0.012989</td>\n",
       "      <td>0.000646</td>\n",
       "      <td>-0.003728</td>\n",
       "      <td>-0.012381</td>\n",
       "      <td>-0.001206</td>\n",
       "      <td>0.001634</td>\n",
       "      <td>-0.044107</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.004696</td>\n",
       "      <td>-0.006955</td>\n",
       "      <td>0.006131</td>\n",
       "      <td>0.007345</td>\n",
       "      <td>0.027692</td>\n",
       "      <td>0.001322</td>\n",
       "      <td>-0.000966</td>\n",
       "      <td>-0.008581</td>\n",
       "      <td>-0.001992</td>\n",
       "      <td>-0.007600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-24 00:00:00+00:00</th>\n",
       "      <td>0.002085</td>\n",
       "      <td>-0.025309</td>\n",
       "      <td>0.003504</td>\n",
       "      <td>0.009594</td>\n",
       "      <td>-0.000323</td>\n",
       "      <td>-0.002336</td>\n",
       "      <td>0.000210</td>\n",
       "      <td>-0.004537</td>\n",
       "      <td>0.000435</td>\n",
       "      <td>0.063741</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000777</td>\n",
       "      <td>0.012960</td>\n",
       "      <td>0.019935</td>\n",
       "      <td>-0.009563</td>\n",
       "      <td>-0.012992</td>\n",
       "      <td>-0.001871</td>\n",
       "      <td>-0.004252</td>\n",
       "      <td>-0.009043</td>\n",
       "      <td>0.002650</td>\n",
       "      <td>-0.000651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-25 00:00:00+00:00</th>\n",
       "      <td>-0.008206</td>\n",
       "      <td>0.001938</td>\n",
       "      <td>0.006805</td>\n",
       "      <td>-0.007151</td>\n",
       "      <td>-0.013744</td>\n",
       "      <td>0.004365</td>\n",
       "      <td>-0.000862</td>\n",
       "      <td>-0.002338</td>\n",
       "      <td>-0.002500</td>\n",
       "      <td>-0.002810</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.008888</td>\n",
       "      <td>-0.004458</td>\n",
       "      <td>-0.007690</td>\n",
       "      <td>-0.002792</td>\n",
       "      <td>-0.001913</td>\n",
       "      <td>0.004824</td>\n",
       "      <td>0.002894</td>\n",
       "      <td>-0.006174</td>\n",
       "      <td>-0.000309</td>\n",
       "      <td>0.000868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-27 00:00:00+00:00</th>\n",
       "      <td>-0.003256</td>\n",
       "      <td>0.009201</td>\n",
       "      <td>0.003285</td>\n",
       "      <td>-0.001863</td>\n",
       "      <td>-0.004803</td>\n",
       "      <td>0.000612</td>\n",
       "      <td>0.000210</td>\n",
       "      <td>0.003363</td>\n",
       "      <td>0.004359</td>\n",
       "      <td>0.003315</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004736</td>\n",
       "      <td>0.004478</td>\n",
       "      <td>-0.000257</td>\n",
       "      <td>0.002633</td>\n",
       "      <td>0.003795</td>\n",
       "      <td>-0.002140</td>\n",
       "      <td>0.005105</td>\n",
       "      <td>-0.002869</td>\n",
       "      <td>0.005013</td>\n",
       "      <td>0.002343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-30 00:00:00+00:00</th>\n",
       "      <td>-0.010209</td>\n",
       "      <td>-0.010321</td>\n",
       "      <td>-0.012798</td>\n",
       "      <td>0.004159</td>\n",
       "      <td>-0.030838</td>\n",
       "      <td>-0.003542</td>\n",
       "      <td>-0.011004</td>\n",
       "      <td>-0.002228</td>\n",
       "      <td>-0.007703</td>\n",
       "      <td>0.019522</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004212</td>\n",
       "      <td>0.009348</td>\n",
       "      <td>0.005294</td>\n",
       "      <td>-0.007363</td>\n",
       "      <td>-0.007524</td>\n",
       "      <td>-0.006928</td>\n",
       "      <td>-0.006183</td>\n",
       "      <td>0.000101</td>\n",
       "      <td>-0.004339</td>\n",
       "      <td>-0.008071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-01 00:00:00+00:00</th>\n",
       "      <td>0.015748</td>\n",
       "      <td>0.048493</td>\n",
       "      <td>-0.002396</td>\n",
       "      <td>-0.008116</td>\n",
       "      <td>0.014957</td>\n",
       "      <td>0.008718</td>\n",
       "      <td>0.012022</td>\n",
       "      <td>0.008480</td>\n",
       "      <td>0.011918</td>\n",
       "      <td>-0.000970</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015192</td>\n",
       "      <td>0.011075</td>\n",
       "      <td>0.002821</td>\n",
       "      <td>0.021600</td>\n",
       "      <td>0.013276</td>\n",
       "      <td>0.008582</td>\n",
       "      <td>0.027170</td>\n",
       "      <td>0.016927</td>\n",
       "      <td>0.015028</td>\n",
       "      <td>0.006632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-02 00:00:00+00:00</th>\n",
       "      <td>-0.005284</td>\n",
       "      <td>0.012930</td>\n",
       "      <td>-0.027166</td>\n",
       "      <td>-0.009030</td>\n",
       "      <td>-0.022022</td>\n",
       "      <td>-0.006534</td>\n",
       "      <td>-0.005287</td>\n",
       "      <td>-0.004991</td>\n",
       "      <td>-0.005727</td>\n",
       "      <td>-0.006990</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.003858</td>\n",
       "      <td>-0.024693</td>\n",
       "      <td>-0.028571</td>\n",
       "      <td>0.007572</td>\n",
       "      <td>-0.029962</td>\n",
       "      <td>-0.018335</td>\n",
       "      <td>0.006313</td>\n",
       "      <td>-0.004473</td>\n",
       "      <td>-0.015448</td>\n",
       "      <td>-0.013610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-03 00:00:00+00:00</th>\n",
       "      <td>-0.009521</td>\n",
       "      <td>-0.012555</td>\n",
       "      <td>-0.019944</td>\n",
       "      <td>-0.009292</td>\n",
       "      <td>-0.027724</td>\n",
       "      <td>-0.001415</td>\n",
       "      <td>-0.023650</td>\n",
       "      <td>-0.015429</td>\n",
       "      <td>-0.022930</td>\n",
       "      <td>-0.027826</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.008294</td>\n",
       "      <td>-0.010820</td>\n",
       "      <td>-0.014327</td>\n",
       "      <td>0.002733</td>\n",
       "      <td>-0.000959</td>\n",
       "      <td>-0.005676</td>\n",
       "      <td>-0.024272</td>\n",
       "      <td>-0.028367</td>\n",
       "      <td>-0.015725</td>\n",
       "      <td>-0.025244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-04 00:00:00+00:00</th>\n",
       "      <td>0.020199</td>\n",
       "      <td>0.039303</td>\n",
       "      <td>0.006779</td>\n",
       "      <td>0.033246</td>\n",
       "      <td>0.018899</td>\n",
       "      <td>0.011957</td>\n",
       "      <td>0.026046</td>\n",
       "      <td>0.029924</td>\n",
       "      <td>0.029696</td>\n",
       "      <td>0.002713</td>\n",
       "      <td>...</td>\n",
       "      <td>0.022211</td>\n",
       "      <td>0.010326</td>\n",
       "      <td>0.005736</td>\n",
       "      <td>0.007495</td>\n",
       "      <td>0.011599</td>\n",
       "      <td>0.024774</td>\n",
       "      <td>0.041159</td>\n",
       "      <td>0.011977</td>\n",
       "      <td>0.024452</td>\n",
       "      <td>0.027882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-07 00:00:00+00:00</th>\n",
       "      <td>-0.000340</td>\n",
       "      <td>0.018020</td>\n",
       "      <td>-0.029578</td>\n",
       "      <td>-0.006298</td>\n",
       "      <td>-0.015921</td>\n",
       "      <td>0.000898</td>\n",
       "      <td>0.005727</td>\n",
       "      <td>-0.001463</td>\n",
       "      <td>-0.032188</td>\n",
       "      <td>-0.011988</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.008791</td>\n",
       "      <td>-0.026122</td>\n",
       "      <td>-0.001900</td>\n",
       "      <td>-0.029576</td>\n",
       "      <td>-0.019647</td>\n",
       "      <td>0.003540</td>\n",
       "      <td>-0.001384</td>\n",
       "      <td>-0.042085</td>\n",
       "      <td>-0.011841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-08 00:00:00+00:00</th>\n",
       "      <td>-0.023307</td>\n",
       "      <td>-0.026876</td>\n",
       "      <td>-0.008866</td>\n",
       "      <td>-0.000425</td>\n",
       "      <td>0.007114</td>\n",
       "      <td>0.004906</td>\n",
       "      <td>-0.000209</td>\n",
       "      <td>-0.000280</td>\n",
       "      <td>0.023661</td>\n",
       "      <td>-0.008216</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.004606</td>\n",
       "      <td>-0.003910</td>\n",
       "      <td>-0.028251</td>\n",
       "      <td>-0.012067</td>\n",
       "      <td>-0.004930</td>\n",
       "      <td>-0.017074</td>\n",
       "      <td>-0.010735</td>\n",
       "      <td>-0.006277</td>\n",
       "      <td>-0.031813</td>\n",
       "      <td>0.000666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-09 00:00:00+00:00</th>\n",
       "      <td>-0.005170</td>\n",
       "      <td>-0.020213</td>\n",
       "      <td>0.022223</td>\n",
       "      <td>-0.022077</td>\n",
       "      <td>-0.011303</td>\n",
       "      <td>0.001984</td>\n",
       "      <td>-0.012948</td>\n",
       "      <td>-0.014876</td>\n",
       "      <td>-0.023550</td>\n",
       "      <td>-0.023608</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.013092</td>\n",
       "      <td>-0.009934</td>\n",
       "      <td>0.013390</td>\n",
       "      <td>-0.021066</td>\n",
       "      <td>-0.009869</td>\n",
       "      <td>-0.000570</td>\n",
       "      <td>-0.023679</td>\n",
       "      <td>0.002205</td>\n",
       "      <td>-0.007490</td>\n",
       "      <td>-0.015900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-10 00:00:00+00:00</th>\n",
       "      <td>0.015039</td>\n",
       "      <td>0.010092</td>\n",
       "      <td>-0.009466</td>\n",
       "      <td>0.004763</td>\n",
       "      <td>-0.004463</td>\n",
       "      <td>0.012720</td>\n",
       "      <td>0.007772</td>\n",
       "      <td>0.002897</td>\n",
       "      <td>-0.006699</td>\n",
       "      <td>0.008821</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.006757</td>\n",
       "      <td>0.001883</td>\n",
       "      <td>0.000798</td>\n",
       "      <td>-0.000317</td>\n",
       "      <td>0.014970</td>\n",
       "      <td>0.012138</td>\n",
       "      <td>-0.008256</td>\n",
       "      <td>-0.000297</td>\n",
       "      <td>0.014759</td>\n",
       "      <td>0.019695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-11 00:00:00+00:00</th>\n",
       "      <td>-0.012227</td>\n",
       "      <td>-0.045356</td>\n",
       "      <td>-0.019179</td>\n",
       "      <td>-0.025740</td>\n",
       "      <td>-0.031185</td>\n",
       "      <td>0.001280</td>\n",
       "      <td>-0.020962</td>\n",
       "      <td>-0.021380</td>\n",
       "      <td>0.027653</td>\n",
       "      <td>-0.003843</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.014938</td>\n",
       "      <td>-0.012713</td>\n",
       "      <td>-0.017840</td>\n",
       "      <td>-0.017755</td>\n",
       "      <td>-0.012793</td>\n",
       "      <td>-0.013062</td>\n",
       "      <td>-0.025836</td>\n",
       "      <td>-0.010112</td>\n",
       "      <td>-0.029782</td>\n",
       "      <td>-0.005856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-14 00:00:00+00:00</th>\n",
       "      <td>-0.011197</td>\n",
       "      <td>-0.007618</td>\n",
       "      <td>-0.008325</td>\n",
       "      <td>-0.006189</td>\n",
       "      <td>0.025898</td>\n",
       "      <td>0.004406</td>\n",
       "      <td>0.010145</td>\n",
       "      <td>0.010071</td>\n",
       "      <td>0.020127</td>\n",
       "      <td>-0.001938</td>\n",
       "      <td>...</td>\n",
       "      <td>0.007216</td>\n",
       "      <td>-0.000941</td>\n",
       "      <td>0.022738</td>\n",
       "      <td>-0.001835</td>\n",
       "      <td>-0.017913</td>\n",
       "      <td>0.011580</td>\n",
       "      <td>0.004910</td>\n",
       "      <td>0.005356</td>\n",
       "      <td>-0.014991</td>\n",
       "      <td>0.016583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-15 00:00:00+00:00</th>\n",
       "      <td>0.024683</td>\n",
       "      <td>0.019768</td>\n",
       "      <td>0.057990</td>\n",
       "      <td>-0.017686</td>\n",
       "      <td>0.017133</td>\n",
       "      <td>-0.008194</td>\n",
       "      <td>0.017415</td>\n",
       "      <td>0.003386</td>\n",
       "      <td>0.008149</td>\n",
       "      <td>-0.004743</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015392</td>\n",
       "      <td>0.013516</td>\n",
       "      <td>0.044710</td>\n",
       "      <td>0.004357</td>\n",
       "      <td>0.016222</td>\n",
       "      <td>0.001635</td>\n",
       "      <td>0.013410</td>\n",
       "      <td>0.015787</td>\n",
       "      <td>0.035626</td>\n",
       "      <td>0.008156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-16 00:00:00+00:00</th>\n",
       "      <td>0.010780</td>\n",
       "      <td>0.014190</td>\n",
       "      <td>0.029771</td>\n",
       "      <td>0.007685</td>\n",
       "      <td>0.021998</td>\n",
       "      <td>-0.000985</td>\n",
       "      <td>0.010080</td>\n",
       "      <td>0.022107</td>\n",
       "      <td>0.016379</td>\n",
       "      <td>0.017336</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004713</td>\n",
       "      <td>0.000531</td>\n",
       "      <td>-0.003522</td>\n",
       "      <td>0.008507</td>\n",
       "      <td>0.024937</td>\n",
       "      <td>0.020719</td>\n",
       "      <td>0.012809</td>\n",
       "      <td>0.008606</td>\n",
       "      <td>0.010755</td>\n",
       "      <td>0.002538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-17 00:00:00+00:00</th>\n",
       "      <td>-0.017212</td>\n",
       "      <td>-0.017122</td>\n",
       "      <td>-0.048190</td>\n",
       "      <td>-0.021196</td>\n",
       "      <td>-0.021696</td>\n",
       "      <td>0.007386</td>\n",
       "      <td>-0.017153</td>\n",
       "      <td>-0.053355</td>\n",
       "      <td>-0.014232</td>\n",
       "      <td>-0.024510</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.001564</td>\n",
       "      <td>-0.018147</td>\n",
       "      <td>-0.015037</td>\n",
       "      <td>-0.003142</td>\n",
       "      <td>-0.007787</td>\n",
       "      <td>-0.026697</td>\n",
       "      <td>-0.018224</td>\n",
       "      <td>-0.011966</td>\n",
       "      <td>-0.015960</td>\n",
       "      <td>-0.007637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-18 00:00:00+00:00</th>\n",
       "      <td>-0.041084</td>\n",
       "      <td>-0.032259</td>\n",
       "      <td>-0.022863</td>\n",
       "      <td>-0.027064</td>\n",
       "      <td>-0.011342</td>\n",
       "      <td>-0.004497</td>\n",
       "      <td>-0.034461</td>\n",
       "      <td>-0.012883</td>\n",
       "      <td>-0.030679</td>\n",
       "      <td>-0.016940</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.019013</td>\n",
       "      <td>-0.012314</td>\n",
       "      <td>-0.008724</td>\n",
       "      <td>-0.010451</td>\n",
       "      <td>-0.003944</td>\n",
       "      <td>-0.017002</td>\n",
       "      <td>-0.004991</td>\n",
       "      <td>-0.017384</td>\n",
       "      <td>-0.037845</td>\n",
       "      <td>-0.002791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-21 00:00:00+00:00</th>\n",
       "      <td>0.009455</td>\n",
       "      <td>0.031863</td>\n",
       "      <td>0.000531</td>\n",
       "      <td>0.012254</td>\n",
       "      <td>0.008245</td>\n",
       "      <td>0.009916</td>\n",
       "      <td>0.007778</td>\n",
       "      <td>0.010404</td>\n",
       "      <td>0.003395</td>\n",
       "      <td>0.011962</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006358</td>\n",
       "      <td>0.016776</td>\n",
       "      <td>-0.000255</td>\n",
       "      <td>0.007035</td>\n",
       "      <td>0.014779</td>\n",
       "      <td>0.008360</td>\n",
       "      <td>0.021714</td>\n",
       "      <td>0.012842</td>\n",
       "      <td>0.002271</td>\n",
       "      <td>0.015894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-22 00:00:00+00:00</th>\n",
       "      <td>0.010502</td>\n",
       "      <td>0.011670</td>\n",
       "      <td>-0.011760</td>\n",
       "      <td>-0.000927</td>\n",
       "      <td>0.024746</td>\n",
       "      <td>0.002617</td>\n",
       "      <td>0.009978</td>\n",
       "      <td>0.007473</td>\n",
       "      <td>0.024012</td>\n",
       "      <td>0.003326</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031671</td>\n",
       "      <td>0.002735</td>\n",
       "      <td>0.005054</td>\n",
       "      <td>0.010047</td>\n",
       "      <td>0.038863</td>\n",
       "      <td>0.009977</td>\n",
       "      <td>-0.005448</td>\n",
       "      <td>0.014966</td>\n",
       "      <td>0.014553</td>\n",
       "      <td>0.008027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-23 00:00:00+00:00</th>\n",
       "      <td>0.011803</td>\n",
       "      <td>0.009219</td>\n",
       "      <td>0.008325</td>\n",
       "      <td>0.012869</td>\n",
       "      <td>0.017178</td>\n",
       "      <td>0.007567</td>\n",
       "      <td>0.013950</td>\n",
       "      <td>0.006365</td>\n",
       "      <td>0.009380</td>\n",
       "      <td>0.008296</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009199</td>\n",
       "      <td>0.009501</td>\n",
       "      <td>0.032702</td>\n",
       "      <td>0.007586</td>\n",
       "      <td>0.011193</td>\n",
       "      <td>0.017237</td>\n",
       "      <td>0.015349</td>\n",
       "      <td>0.010219</td>\n",
       "      <td>0.018773</td>\n",
       "      <td>0.005444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-24 00:00:00+00:00</th>\n",
       "      <td>-0.003682</td>\n",
       "      <td>0.012022</td>\n",
       "      <td>0.000465</td>\n",
       "      <td>-0.005341</td>\n",
       "      <td>-0.002041</td>\n",
       "      <td>0.000090</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.001820</td>\n",
       "      <td>-0.004224</td>\n",
       "      <td>0.005673</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009623</td>\n",
       "      <td>-0.000620</td>\n",
       "      <td>-0.010724</td>\n",
       "      <td>-0.002127</td>\n",
       "      <td>0.005553</td>\n",
       "      <td>-0.001614</td>\n",
       "      <td>-0.001620</td>\n",
       "      <td>0.001364</td>\n",
       "      <td>0.003975</td>\n",
       "      <td>0.003121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-28 00:00:00+00:00</th>\n",
       "      <td>0.007040</td>\n",
       "      <td>-0.013259</td>\n",
       "      <td>0.009526</td>\n",
       "      <td>-0.011204</td>\n",
       "      <td>0.004953</td>\n",
       "      <td>0.002309</td>\n",
       "      <td>-0.001550</td>\n",
       "      <td>-0.001441</td>\n",
       "      <td>-0.001060</td>\n",
       "      <td>-0.006164</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000503</td>\n",
       "      <td>-0.001064</td>\n",
       "      <td>-0.007439</td>\n",
       "      <td>0.004930</td>\n",
       "      <td>-0.021138</td>\n",
       "      <td>-0.003484</td>\n",
       "      <td>-0.002177</td>\n",
       "      <td>-0.006413</td>\n",
       "      <td>-0.005033</td>\n",
       "      <td>-0.004784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-29 00:00:00+00:00</th>\n",
       "      <td>0.019443</td>\n",
       "      <td>0.006256</td>\n",
       "      <td>0.010957</td>\n",
       "      <td>0.017976</td>\n",
       "      <td>0.011911</td>\n",
       "      <td>0.005569</td>\n",
       "      <td>0.017542</td>\n",
       "      <td>0.011914</td>\n",
       "      <td>0.011996</td>\n",
       "      <td>0.015224</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013813</td>\n",
       "      <td>0.007964</td>\n",
       "      <td>0.005336</td>\n",
       "      <td>0.011436</td>\n",
       "      <td>0.011283</td>\n",
       "      <td>0.004307</td>\n",
       "      <td>0.005415</td>\n",
       "      <td>0.007235</td>\n",
       "      <td>0.006174</td>\n",
       "      <td>0.008997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-30 00:00:00+00:00</th>\n",
       "      <td>-0.006384</td>\n",
       "      <td>-0.016085</td>\n",
       "      <td>-0.005254</td>\n",
       "      <td>-0.013056</td>\n",
       "      <td>0.005904</td>\n",
       "      <td>0.002391</td>\n",
       "      <td>-0.012017</td>\n",
       "      <td>0.005124</td>\n",
       "      <td>-0.000524</td>\n",
       "      <td>-0.013256</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.014617</td>\n",
       "      <td>-0.007064</td>\n",
       "      <td>-0.013261</td>\n",
       "      <td>-0.008079</td>\n",
       "      <td>0.001847</td>\n",
       "      <td>-0.006182</td>\n",
       "      <td>-0.005781</td>\n",
       "      <td>-0.002921</td>\n",
       "      <td>-0.012235</td>\n",
       "      <td>-0.001454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31 00:00:00+00:00</th>\n",
       "      <td>-0.012432</td>\n",
       "      <td>-0.010532</td>\n",
       "      <td>-0.005879</td>\n",
       "      <td>-0.019199</td>\n",
       "      <td>-0.009372</td>\n",
       "      <td>-0.012481</td>\n",
       "      <td>-0.007953</td>\n",
       "      <td>-0.012844</td>\n",
       "      <td>-0.014064</td>\n",
       "      <td>-0.021745</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.016052</td>\n",
       "      <td>-0.018175</td>\n",
       "      <td>-0.002050</td>\n",
       "      <td>-0.009119</td>\n",
       "      <td>-0.008371</td>\n",
       "      <td>-0.010031</td>\n",
       "      <td>-0.010299</td>\n",
       "      <td>0.001176</td>\n",
       "      <td>-0.006212</td>\n",
       "      <td>-0.007051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-04 00:00:00+00:00</th>\n",
       "      <td>-0.028282</td>\n",
       "      <td>-0.033988</td>\n",
       "      <td>0.011494</td>\n",
       "      <td>0.000855</td>\n",
       "      <td>-0.027512</td>\n",
       "      <td>-0.017741</td>\n",
       "      <td>-0.044067</td>\n",
       "      <td>-0.025551</td>\n",
       "      <td>-0.020971</td>\n",
       "      <td>-0.015919</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.024767</td>\n",
       "      <td>-0.024922</td>\n",
       "      <td>-0.006276</td>\n",
       "      <td>-0.032711</td>\n",
       "      <td>-0.031051</td>\n",
       "      <td>-0.011520</td>\n",
       "      <td>-0.011489</td>\n",
       "      <td>-0.007604</td>\n",
       "      <td>-0.021614</td>\n",
       "      <td>-0.013564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-05 00:00:00+00:00</th>\n",
       "      <td>0.004058</td>\n",
       "      <td>-0.009541</td>\n",
       "      <td>-0.006830</td>\n",
       "      <td>-0.025054</td>\n",
       "      <td>-0.004169</td>\n",
       "      <td>0.014629</td>\n",
       "      <td>-0.000247</td>\n",
       "      <td>0.005207</td>\n",
       "      <td>0.004023</td>\n",
       "      <td>-0.007347</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002098</td>\n",
       "      <td>0.014863</td>\n",
       "      <td>0.008511</td>\n",
       "      <td>0.020390</td>\n",
       "      <td>-0.001957</td>\n",
       "      <td>-0.000286</td>\n",
       "      <td>-0.002495</td>\n",
       "      <td>0.020820</td>\n",
       "      <td>-0.010853</td>\n",
       "      <td>0.015647</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1256 rows × 490 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Equity(0 [A])  Equity(1 [AAL])  Equity(2 [AAP])  \\\n",
       "2011-01-07 00:00:00+00:00       0.008437         0.014230         0.026702   \n",
       "2011-01-10 00:00:00+00:00      -0.004174         0.006195         0.007435   \n",
       "2011-01-11 00:00:00+00:00      -0.001886        -0.043644        -0.005927   \n",
       "2011-01-12 00:00:00+00:00       0.017254        -0.008237         0.013387   \n",
       "2011-01-13 00:00:00+00:00      -0.004559         0.000955         0.003031   \n",
       "2011-01-14 00:00:00+00:00       0.003439        -0.009156         0.003022   \n",
       "2011-01-18 00:00:00+00:00       0.034254        -0.062085        -0.004286   \n",
       "2011-01-19 00:00:00+00:00      -0.010224        -0.008929         0.008754   \n",
       "2011-01-20 00:00:00+00:00      -0.008496         0.021953        -0.004732   \n",
       "2011-01-21 00:00:00+00:00       0.007873        -0.041038         0.005544   \n",
       "2011-01-24 00:00:00+00:00       0.014646         0.027473        -0.001106   \n",
       "2011-01-25 00:00:00+00:00      -0.006736         0.002982         0.009146   \n",
       "2011-01-26 00:00:00+00:00      -0.030736         0.066133         0.003593   \n",
       "2011-01-27 00:00:00+00:00       0.007721         0.023178        -0.001553   \n",
       "2011-01-28 00:00:00+00:00      -0.018846        -0.080553        -0.000936   \n",
       "2011-01-31 00:00:00+00:00       0.003608        -0.023615        -0.002351   \n",
       "2011-02-01 00:00:00+00:00       0.011654        -0.001047        -0.009218   \n",
       "2011-02-02 00:00:00+00:00       0.010112        -0.039304        -0.027477   \n",
       "2011-02-03 00:00:00+00:00      -0.000289         0.007310         0.014126   \n",
       "2011-02-04 00:00:00+00:00       0.005627        -0.036500         0.024014   \n",
       "2011-02-07 00:00:00+00:00       0.007709         0.052046         0.008114   \n",
       "2011-02-08 00:00:00+00:00       0.010854         0.016455         0.006202   \n",
       "2011-02-09 00:00:00+00:00       0.004664         0.000000         0.016955   \n",
       "2011-02-10 00:00:00+00:00       0.000413        -0.003048        -0.011367   \n",
       "2011-02-11 00:00:00+00:00      -0.007150         0.028364         0.000764   \n",
       "2011-02-14 00:00:00+00:00       0.001663        -0.015790        -0.023274   \n",
       "2011-02-15 00:00:00+00:00      -0.011905         0.011043        -0.003926   \n",
       "2011-02-16 00:00:00+00:00       0.015123         0.001958         0.013860   \n",
       "2011-02-17 00:00:00+00:00      -0.003311        -0.017791        -0.024844   \n",
       "2011-02-18 00:00:00+00:00       0.011078        -0.020103        -0.006693   \n",
       "...                                  ...              ...              ...   \n",
       "2015-11-20 00:00:00+00:00       0.001072        -0.002373         0.002767   \n",
       "2015-11-23 00:00:00+00:00      -0.007094         0.002379        -0.001228   \n",
       "2015-11-24 00:00:00+00:00       0.002085        -0.025309         0.003504   \n",
       "2015-11-25 00:00:00+00:00      -0.008206         0.001938         0.006805   \n",
       "2015-11-27 00:00:00+00:00      -0.003256         0.009201         0.003285   \n",
       "2015-11-30 00:00:00+00:00      -0.010209        -0.010321        -0.012798   \n",
       "2015-12-01 00:00:00+00:00       0.015748         0.048493        -0.002396   \n",
       "2015-12-02 00:00:00+00:00      -0.005284         0.012930        -0.027166   \n",
       "2015-12-03 00:00:00+00:00      -0.009521        -0.012555        -0.019944   \n",
       "2015-12-04 00:00:00+00:00       0.020199         0.039303         0.006779   \n",
       "2015-12-07 00:00:00+00:00      -0.000340         0.018020        -0.029578   \n",
       "2015-12-08 00:00:00+00:00      -0.023307        -0.026876        -0.008866   \n",
       "2015-12-09 00:00:00+00:00      -0.005170        -0.020213         0.022223   \n",
       "2015-12-10 00:00:00+00:00       0.015039         0.010092        -0.009466   \n",
       "2015-12-11 00:00:00+00:00      -0.012227        -0.045356        -0.019179   \n",
       "2015-12-14 00:00:00+00:00      -0.011197        -0.007618        -0.008325   \n",
       "2015-12-15 00:00:00+00:00       0.024683         0.019768         0.057990   \n",
       "2015-12-16 00:00:00+00:00       0.010780         0.014190         0.029771   \n",
       "2015-12-17 00:00:00+00:00      -0.017212        -0.017122        -0.048190   \n",
       "2015-12-18 00:00:00+00:00      -0.041084        -0.032259        -0.022863   \n",
       "2015-12-21 00:00:00+00:00       0.009455         0.031863         0.000531   \n",
       "2015-12-22 00:00:00+00:00       0.010502         0.011670        -0.011760   \n",
       "2015-12-23 00:00:00+00:00       0.011803         0.009219         0.008325   \n",
       "2015-12-24 00:00:00+00:00      -0.003682         0.012022         0.000465   \n",
       "2015-12-28 00:00:00+00:00       0.007040        -0.013259         0.009526   \n",
       "2015-12-29 00:00:00+00:00       0.019443         0.006256         0.010957   \n",
       "2015-12-30 00:00:00+00:00      -0.006384        -0.016085        -0.005254   \n",
       "2015-12-31 00:00:00+00:00      -0.012432        -0.010532        -0.005879   \n",
       "2016-01-04 00:00:00+00:00      -0.028282        -0.033988         0.011494   \n",
       "2016-01-05 00:00:00+00:00       0.004058        -0.009541        -0.006830   \n",
       "\n",
       "                           Equity(3 [AAPL])  Equity(4 [ABBV])  \\\n",
       "2011-01-07 00:00:00+00:00          0.007146          0.000000   \n",
       "2011-01-10 00:00:00+00:00          0.018852          0.000000   \n",
       "2011-01-11 00:00:00+00:00         -0.002367          0.000000   \n",
       "2011-01-12 00:00:00+00:00          0.008133          0.000000   \n",
       "2011-01-13 00:00:00+00:00          0.003657          0.000000   \n",
       "2011-01-14 00:00:00+00:00          0.008106          0.000000   \n",
       "2011-01-18 00:00:00+00:00         -0.022474          0.000000   \n",
       "2011-01-19 00:00:00+00:00         -0.005314          0.000000   \n",
       "2011-01-20 00:00:00+00:00         -0.018189          0.000000   \n",
       "2011-01-21 00:00:00+00:00         -0.017911          0.000000   \n",
       "2011-01-24 00:00:00+00:00          0.032837          0.000000   \n",
       "2011-01-25 00:00:00+00:00          0.011710          0.000000   \n",
       "2011-01-26 00:00:00+00:00          0.007193          0.000000   \n",
       "2011-01-27 00:00:00+00:00         -0.001877          0.000000   \n",
       "2011-01-28 00:00:00+00:00         -0.020710          0.000000   \n",
       "2011-01-31 00:00:00+00:00          0.009578          0.000000   \n",
       "2011-02-01 00:00:00+00:00          0.016818          0.000000   \n",
       "2011-02-02 00:00:00+00:00         -0.002053          0.000000   \n",
       "2011-02-03 00:00:00+00:00         -0.002560          0.000000   \n",
       "2011-02-04 00:00:00+00:00          0.008915          0.000000   \n",
       "2011-02-07 00:00:00+00:00          0.015538          0.000000   \n",
       "2011-02-08 00:00:00+00:00          0.009440          0.000000   \n",
       "2011-02-09 00:00:00+00:00          0.008332          0.000000   \n",
       "2011-02-10 00:00:00+00:00         -0.010109          0.000000   \n",
       "2011-02-11 00:00:00+00:00          0.006505          0.000000   \n",
       "2011-02-14 00:00:00+00:00          0.006529          0.000000   \n",
       "2011-02-15 00:00:00+00:00          0.002016          0.000000   \n",
       "2011-02-16 00:00:00+00:00          0.008967          0.000000   \n",
       "2011-02-17 00:00:00+00:00         -0.013309          0.000000   \n",
       "2011-02-18 00:00:00+00:00         -0.021595          0.000000   \n",
       "...                                     ...               ...   \n",
       "2015-11-20 00:00:00+00:00          0.004381          0.009256   \n",
       "2015-11-23 00:00:00+00:00         -0.012989          0.000646   \n",
       "2015-11-24 00:00:00+00:00          0.009594         -0.000323   \n",
       "2015-11-25 00:00:00+00:00         -0.007151         -0.013744   \n",
       "2015-11-27 00:00:00+00:00         -0.001863         -0.004803   \n",
       "2015-11-30 00:00:00+00:00          0.004159         -0.030838   \n",
       "2015-12-01 00:00:00+00:00         -0.008116          0.014957   \n",
       "2015-12-02 00:00:00+00:00         -0.009030         -0.022022   \n",
       "2015-12-03 00:00:00+00:00         -0.009292         -0.027724   \n",
       "2015-12-04 00:00:00+00:00          0.033246          0.018899   \n",
       "2015-12-07 00:00:00+00:00         -0.006298         -0.015921   \n",
       "2015-12-08 00:00:00+00:00         -0.000425          0.007114   \n",
       "2015-12-09 00:00:00+00:00         -0.022077         -0.011303   \n",
       "2015-12-10 00:00:00+00:00          0.004763         -0.004463   \n",
       "2015-12-11 00:00:00+00:00         -0.025740         -0.031185   \n",
       "2015-12-14 00:00:00+00:00         -0.006189          0.025898   \n",
       "2015-12-15 00:00:00+00:00         -0.017686          0.017133   \n",
       "2015-12-16 00:00:00+00:00          0.007685          0.021998   \n",
       "2015-12-17 00:00:00+00:00         -0.021196         -0.021696   \n",
       "2015-12-18 00:00:00+00:00         -0.027064         -0.011342   \n",
       "2015-12-21 00:00:00+00:00          0.012254          0.008245   \n",
       "2015-12-22 00:00:00+00:00         -0.000927          0.024746   \n",
       "2015-12-23 00:00:00+00:00          0.012869          0.017178   \n",
       "2015-12-24 00:00:00+00:00         -0.005341         -0.002041   \n",
       "2015-12-28 00:00:00+00:00         -0.011204          0.004953   \n",
       "2015-12-29 00:00:00+00:00          0.017976          0.011911   \n",
       "2015-12-30 00:00:00+00:00         -0.013056          0.005904   \n",
       "2015-12-31 00:00:00+00:00         -0.019199         -0.009372   \n",
       "2016-01-04 00:00:00+00:00          0.000855         -0.027512   \n",
       "2016-01-05 00:00:00+00:00         -0.025054         -0.004169   \n",
       "\n",
       "                           Equity(5 [ABC])  Equity(6 [ABT])  Equity(7 [ACN])  \\\n",
       "2011-01-07 00:00:00+00:00         0.001994         0.004165         0.001648   \n",
       "2011-01-10 00:00:00+00:00        -0.005714        -0.008896        -0.008854   \n",
       "2011-01-11 00:00:00+00:00         0.009783        -0.002067         0.013717   \n",
       "2011-01-12 00:00:00+00:00        -0.005979        -0.001011         0.022969   \n",
       "2011-01-13 00:00:00+00:00         0.014925        -0.004451        -0.000400   \n",
       "2011-01-14 00:00:00+00:00         0.001395        -0.010111         0.002590   \n",
       "2011-01-18 00:00:00+00:00         0.020889         0.006621         0.006998   \n",
       "2011-01-19 00:00:00+00:00        -0.017144         0.002753        -0.002962   \n",
       "2011-01-20 00:00:00+00:00         0.004794         0.013322         0.018713   \n",
       "2011-01-21 00:00:00+00:00         0.010642        -0.000853        -0.001952   \n",
       "2011-01-24 00:00:00+00:00         0.005249         0.005223         0.008420   \n",
       "2011-01-25 00:00:00+00:00        -0.009363        -0.004347         0.004859   \n",
       "2011-01-26 00:00:00+00:00         0.012227        -0.025241         0.012192   \n",
       "2011-01-27 00:00:00+00:00         0.011833        -0.007928         0.000179   \n",
       "2011-01-28 00:00:00+00:00        -0.022262        -0.019200        -0.016035   \n",
       "2011-01-31 00:00:00+00:00        -0.003893        -0.007248        -0.000980   \n",
       "2011-02-01 00:00:00+00:00         0.011976         0.001546         0.017498   \n",
       "2011-02-02 00:00:00+00:00        -0.021197         0.011068         0.003632   \n",
       "2011-02-03 00:00:00+00:00        -0.003662         0.005894         0.004178   \n",
       "2011-02-04 00:00:00+00:00         0.033047         0.002616        -0.004360   \n",
       "2011-02-07 00:00:00+00:00        -0.002178        -0.009341         0.002279   \n",
       "2011-02-08 00:00:00+00:00         0.002182        -0.001738        -0.000557   \n",
       "2011-02-09 00:00:00+00:00         0.003006        -0.001530         0.001138   \n",
       "2011-02-10 00:00:00+00:00         0.001101        -0.001110         0.005503   \n",
       "2011-02-11 00:00:00+00:00        -0.001375         0.001534        -0.011146   \n",
       "2011-02-14 00:00:00+00:00         0.005750         0.009245         0.000202   \n",
       "2011-02-15 00:00:00+00:00        -0.007329         0.016750        -0.008021   \n",
       "2011-02-16 00:00:00+00:00        -0.003554        -0.010502         0.027329   \n",
       "2011-02-17 00:00:00+00:00         0.029148         0.001301         0.011784   \n",
       "2011-02-18 00:00:00+00:00         0.009620         0.012106        -0.007953   \n",
       "...                                    ...              ...              ...   \n",
       "2015-11-20 00:00:00+00:00        -0.000905         0.006113         0.006430   \n",
       "2015-11-23 00:00:00+00:00        -0.003728        -0.012381        -0.001206   \n",
       "2015-11-24 00:00:00+00:00        -0.002336         0.000210        -0.004537   \n",
       "2015-11-25 00:00:00+00:00         0.004365        -0.000862        -0.002338   \n",
       "2015-11-27 00:00:00+00:00         0.000612         0.000210         0.003363   \n",
       "2015-11-30 00:00:00+00:00        -0.003542        -0.011004        -0.002228   \n",
       "2015-12-01 00:00:00+00:00         0.008718         0.012022         0.008480   \n",
       "2015-12-02 00:00:00+00:00        -0.006534        -0.005287        -0.004991   \n",
       "2015-12-03 00:00:00+00:00        -0.001415        -0.023650        -0.015429   \n",
       "2015-12-04 00:00:00+00:00         0.011957         0.026046         0.029924   \n",
       "2015-12-07 00:00:00+00:00         0.000898         0.005727        -0.001463   \n",
       "2015-12-08 00:00:00+00:00         0.004906        -0.000209        -0.000280   \n",
       "2015-12-09 00:00:00+00:00         0.001984        -0.012948        -0.014876   \n",
       "2015-12-10 00:00:00+00:00         0.012720         0.007772         0.002897   \n",
       "2015-12-11 00:00:00+00:00         0.001280        -0.020962        -0.021380   \n",
       "2015-12-14 00:00:00+00:00         0.004406         0.010145         0.010071   \n",
       "2015-12-15 00:00:00+00:00        -0.008194         0.017415         0.003386   \n",
       "2015-12-16 00:00:00+00:00        -0.000985         0.010080         0.022107   \n",
       "2015-12-17 00:00:00+00:00         0.007386        -0.017153        -0.053355   \n",
       "2015-12-18 00:00:00+00:00        -0.004497        -0.034461        -0.012883   \n",
       "2015-12-21 00:00:00+00:00         0.009916         0.007778         0.010404   \n",
       "2015-12-22 00:00:00+00:00         0.002617         0.009978         0.007473   \n",
       "2015-12-23 00:00:00+00:00         0.007567         0.013950         0.006365   \n",
       "2015-12-24 00:00:00+00:00         0.000090         0.000000        -0.001820   \n",
       "2015-12-28 00:00:00+00:00         0.002309        -0.001550        -0.001441   \n",
       "2015-12-29 00:00:00+00:00         0.005569         0.017542         0.011914   \n",
       "2015-12-30 00:00:00+00:00         0.002391        -0.012017         0.005124   \n",
       "2015-12-31 00:00:00+00:00        -0.012481        -0.007953        -0.012844   \n",
       "2016-01-04 00:00:00+00:00        -0.017741        -0.044067        -0.025551   \n",
       "2016-01-05 00:00:00+00:00         0.014629        -0.000247         0.005207   \n",
       "\n",
       "                           Equity(8 [ADBE])  Equity(9 [ADI])  \\\n",
       "2011-01-07 00:00:00+00:00         -0.007127        -0.005818   \n",
       "2011-01-10 00:00:00+00:00          0.028714         0.002926   \n",
       "2011-01-11 00:00:00+00:00          0.000607         0.008753   \n",
       "2011-01-12 00:00:00+00:00          0.017950         0.000257   \n",
       "2011-01-13 00:00:00+00:00         -0.005719        -0.005012   \n",
       "2011-01-14 00:00:00+00:00          0.012283         0.019827   \n",
       "2011-01-18 00:00:00+00:00          0.011542         0.032645   \n",
       "2011-01-19 00:00:00+00:00         -0.007899        -0.020575   \n",
       "2011-01-20 00:00:00+00:00         -0.012386        -0.002818   \n",
       "2011-01-21 00:00:00+00:00         -0.006569        -0.004113   \n",
       "2011-01-24 00:00:00+00:00          0.022843         0.014974   \n",
       "2011-01-25 00:00:00+00:00         -0.013811        -0.014505   \n",
       "2011-01-26 00:00:00+00:00         -0.001192         0.002837   \n",
       "2011-01-27 00:00:00+00:00          0.009845         0.007480   \n",
       "2011-01-28 00:00:00+00:00         -0.040177        -0.022460   \n",
       "2011-01-31 00:00:00+00:00          0.017236         0.013818   \n",
       "2011-02-01 00:00:00+00:00          0.013918         0.021624   \n",
       "2011-02-02 00:00:00+00:00         -0.002387         0.002280   \n",
       "2011-02-03 00:00:00+00:00          0.002991        -0.013341   \n",
       "2011-02-04 00:00:00+00:00         -0.005070         0.019659   \n",
       "2011-02-07 00:00:00+00:00          0.005995        -0.003514   \n",
       "2011-02-08 00:00:00+00:00          0.000298        -0.006010   \n",
       "2011-02-09 00:00:00+00:00         -0.016682         0.004781   \n",
       "2011-02-10 00:00:00+00:00          0.016965         0.004513   \n",
       "2011-02-11 00:00:00+00:00          0.002979         0.015007   \n",
       "2011-02-14 00:00:00+00:00          0.005643         0.009877   \n",
       "2011-02-15 00:00:00+00:00          0.002363         0.000239   \n",
       "2011-02-16 00:00:00+00:00          0.022098        -0.003905   \n",
       "2011-02-17 00:00:00+00:00          0.008360         0.008559   \n",
       "2011-02-18 00:00:00+00:00          0.011721        -0.001691   \n",
       "...                                     ...              ...   \n",
       "2015-11-20 00:00:00+00:00          0.000545        -0.005843   \n",
       "2015-11-23 00:00:00+00:00          0.001634        -0.044107   \n",
       "2015-11-24 00:00:00+00:00          0.000435         0.063741   \n",
       "2015-11-25 00:00:00+00:00         -0.002500        -0.002810   \n",
       "2015-11-27 00:00:00+00:00          0.004359         0.003315   \n",
       "2015-11-30 00:00:00+00:00         -0.007703         0.019522   \n",
       "2015-12-01 00:00:00+00:00          0.011918        -0.000970   \n",
       "2015-12-02 00:00:00+00:00         -0.005727        -0.006990   \n",
       "2015-12-03 00:00:00+00:00         -0.022930        -0.027826   \n",
       "2015-12-04 00:00:00+00:00          0.029696         0.002713   \n",
       "2015-12-07 00:00:00+00:00         -0.032188        -0.011988   \n",
       "2015-12-08 00:00:00+00:00          0.023661        -0.008216   \n",
       "2015-12-09 00:00:00+00:00         -0.023550        -0.023608   \n",
       "2015-12-10 00:00:00+00:00         -0.006699         0.008821   \n",
       "2015-12-11 00:00:00+00:00          0.027653        -0.003843   \n",
       "2015-12-14 00:00:00+00:00          0.020127        -0.001938   \n",
       "2015-12-15 00:00:00+00:00          0.008149        -0.004743   \n",
       "2015-12-16 00:00:00+00:00          0.016379         0.017336   \n",
       "2015-12-17 00:00:00+00:00         -0.014232        -0.024510   \n",
       "2015-12-18 00:00:00+00:00         -0.030679        -0.016940   \n",
       "2015-12-21 00:00:00+00:00          0.003395         0.011962   \n",
       "2015-12-22 00:00:00+00:00          0.024012         0.003326   \n",
       "2015-12-23 00:00:00+00:00          0.009380         0.008296   \n",
       "2015-12-24 00:00:00+00:00         -0.004224         0.005673   \n",
       "2015-12-28 00:00:00+00:00         -0.001060        -0.006164   \n",
       "2015-12-29 00:00:00+00:00          0.011996         0.015224   \n",
       "2015-12-30 00:00:00+00:00         -0.000524        -0.013256   \n",
       "2015-12-31 00:00:00+00:00         -0.014064        -0.021745   \n",
       "2016-01-04 00:00:00+00:00         -0.020971        -0.015919   \n",
       "2016-01-05 00:00:00+00:00          0.004023        -0.007347   \n",
       "\n",
       "                                 ...          Equity(481 [XL])  \\\n",
       "2011-01-07 00:00:00+00:00        ...                 -0.001838   \n",
       "2011-01-10 00:00:00+00:00        ...                  0.000947   \n",
       "2011-01-11 00:00:00+00:00        ...                  0.001314   \n",
       "2011-01-12 00:00:00+00:00        ...                  0.004986   \n",
       "2011-01-13 00:00:00+00:00        ...                  0.030499   \n",
       "2011-01-14 00:00:00+00:00        ...                  0.026607   \n",
       "2011-01-18 00:00:00+00:00        ...                  0.001678   \n",
       "2011-01-19 00:00:00+00:00        ...                 -0.014834   \n",
       "2011-01-20 00:00:00+00:00        ...                 -0.024512   \n",
       "2011-01-21 00:00:00+00:00        ...                  0.000000   \n",
       "2011-01-24 00:00:00+00:00        ...                  0.012359   \n",
       "2011-01-25 00:00:00+00:00        ...                  0.002178   \n",
       "2011-01-26 00:00:00+00:00        ...                  0.002628   \n",
       "2011-01-27 00:00:00+00:00        ...                  0.014267   \n",
       "2011-01-28 00:00:00+00:00        ...                 -0.025647   \n",
       "2011-01-31 00:00:00+00:00        ...                  0.004846   \n",
       "2011-02-01 00:00:00+00:00        ...                  0.015687   \n",
       "2011-02-02 00:00:00+00:00        ...                 -0.012846   \n",
       "2011-02-03 00:00:00+00:00        ...                  0.010430   \n",
       "2011-02-04 00:00:00+00:00        ...                  0.009471   \n",
       "2011-02-07 00:00:00+00:00        ...                  0.006801   \n",
       "2011-02-08 00:00:00+00:00        ...                  0.003846   \n",
       "2011-02-09 00:00:00+00:00        ...                 -0.011837   \n",
       "2011-02-10 00:00:00+00:00        ...                 -0.008947   \n",
       "2011-02-11 00:00:00+00:00        ...                  0.001705   \n",
       "2011-02-14 00:00:00+00:00        ...                 -0.011616   \n",
       "2011-02-15 00:00:00+00:00        ...                 -0.006079   \n",
       "2011-02-16 00:00:00+00:00        ...                  0.009174   \n",
       "2011-02-17 00:00:00+00:00        ...                  0.015656   \n",
       "2011-02-18 00:00:00+00:00        ...                  0.053404   \n",
       "...                              ...                       ...   \n",
       "2015-11-20 00:00:00+00:00        ...                  0.008131   \n",
       "2015-11-23 00:00:00+00:00        ...                 -0.004696   \n",
       "2015-11-24 00:00:00+00:00        ...                 -0.000777   \n",
       "2015-11-25 00:00:00+00:00        ...                 -0.008888   \n",
       "2015-11-27 00:00:00+00:00        ...                  0.004736   \n",
       "2015-11-30 00:00:00+00:00        ...                  0.004212   \n",
       "2015-12-01 00:00:00+00:00        ...                  0.015192   \n",
       "2015-12-02 00:00:00+00:00        ...                 -0.003858   \n",
       "2015-12-03 00:00:00+00:00        ...                 -0.008294   \n",
       "2015-12-04 00:00:00+00:00        ...                  0.022211   \n",
       "2015-12-07 00:00:00+00:00        ...                  0.000000   \n",
       "2015-12-08 00:00:00+00:00        ...                 -0.004606   \n",
       "2015-12-09 00:00:00+00:00        ...                 -0.013092   \n",
       "2015-12-10 00:00:00+00:00        ...                 -0.006757   \n",
       "2015-12-11 00:00:00+00:00        ...                 -0.014938   \n",
       "2015-12-14 00:00:00+00:00        ...                  0.007216   \n",
       "2015-12-15 00:00:00+00:00        ...                  0.015392   \n",
       "2015-12-16 00:00:00+00:00        ...                  0.004713   \n",
       "2015-12-17 00:00:00+00:00        ...                 -0.001564   \n",
       "2015-12-18 00:00:00+00:00        ...                 -0.019013   \n",
       "2015-12-21 00:00:00+00:00        ...                  0.006358   \n",
       "2015-12-22 00:00:00+00:00        ...                  0.031671   \n",
       "2015-12-23 00:00:00+00:00        ...                  0.009199   \n",
       "2015-12-24 00:00:00+00:00        ...                  0.009623   \n",
       "2015-12-28 00:00:00+00:00        ...                  0.000503   \n",
       "2015-12-29 00:00:00+00:00        ...                  0.013813   \n",
       "2015-12-30 00:00:00+00:00        ...                 -0.014617   \n",
       "2015-12-31 00:00:00+00:00        ...                 -0.016052   \n",
       "2016-01-04 00:00:00+00:00        ...                 -0.024767   \n",
       "2016-01-05 00:00:00+00:00        ...                  0.002098   \n",
       "\n",
       "                           Equity(482 [XLNX])  Equity(483 [XOM])  \\\n",
       "2011-01-07 00:00:00+00:00           -0.005619           0.005461   \n",
       "2011-01-10 00:00:00+00:00            0.007814          -0.006081   \n",
       "2011-01-11 00:00:00+00:00            0.010179           0.007442   \n",
       "2011-01-12 00:00:00+00:00            0.015666           0.011763   \n",
       "2011-01-13 00:00:00+00:00           -0.003217           0.001694   \n",
       "2011-01-14 00:00:00+00:00            0.025894           0.014743   \n",
       "2011-01-18 00:00:00+00:00            0.002501           0.011163   \n",
       "2011-01-19 00:00:00+00:00           -0.023590          -0.005968   \n",
       "2011-01-20 00:00:00+00:00            0.007744          -0.006261   \n",
       "2011-01-21 00:00:00+00:00            0.000615           0.015825   \n",
       "2011-01-24 00:00:00+00:00            0.016011          -0.004943   \n",
       "2011-01-25 00:00:00+00:00            0.006273           0.001154   \n",
       "2011-01-26 00:00:00+00:00            0.005934           0.012453   \n",
       "2011-01-27 00:00:00+00:00            0.021169           0.002751   \n",
       "2011-01-28 00:00:00+00:00           -0.020108          -0.011131   \n",
       "2011-01-31 00:00:00+00:00            0.000298           0.021396   \n",
       "2011-02-01 00:00:00+00:00            0.032003           0.040037   \n",
       "2011-02-02 00:00:00+00:00           -0.004518          -0.005958   \n",
       "2011-02-03 00:00:00+00:00           -0.008169           0.000347   \n",
       "2011-02-04 00:00:00+00:00            0.024709          -0.001917   \n",
       "2011-02-07 00:00:00+00:00           -0.005073           0.007803   \n",
       "2011-02-08 00:00:00+00:00            0.001795          -0.006077   \n",
       "2011-02-09 00:00:00+00:00           -0.001792          -0.005178   \n",
       "2011-02-10 00:00:00+00:00            0.003914           0.007876   \n",
       "2011-02-11 00:00:00+00:00            0.010765          -0.004562   \n",
       "2011-02-14 00:00:00+00:00            0.000318           0.025230   \n",
       "2011-02-15 00:00:00+00:00           -0.001804          -0.022853   \n",
       "2011-02-16 00:00:00+00:00            0.003863           0.008682   \n",
       "2011-02-17 00:00:00+00:00            0.000318           0.002275   \n",
       "2011-02-18 00:00:00+00:00            0.001447           0.007393   \n",
       "...                                       ...                ...   \n",
       "2015-11-20 00:00:00+00:00            0.000412          -0.006352   \n",
       "2015-11-23 00:00:00+00:00           -0.006955           0.006131   \n",
       "2015-11-24 00:00:00+00:00            0.012960           0.019935   \n",
       "2015-11-25 00:00:00+00:00           -0.004458          -0.007690   \n",
       "2015-11-27 00:00:00+00:00            0.004478          -0.000257   \n",
       "2015-11-30 00:00:00+00:00            0.009348           0.005294   \n",
       "2015-12-01 00:00:00+00:00            0.011075           0.002821   \n",
       "2015-12-02 00:00:00+00:00           -0.024693          -0.028571   \n",
       "2015-12-03 00:00:00+00:00           -0.010820          -0.014327   \n",
       "2015-12-04 00:00:00+00:00            0.010326           0.005736   \n",
       "2015-12-07 00:00:00+00:00           -0.008791          -0.026122   \n",
       "2015-12-08 00:00:00+00:00           -0.003910          -0.028251   \n",
       "2015-12-09 00:00:00+00:00           -0.009934           0.013390   \n",
       "2015-12-10 00:00:00+00:00            0.001883           0.000798   \n",
       "2015-12-11 00:00:00+00:00           -0.012713          -0.017840   \n",
       "2015-12-14 00:00:00+00:00           -0.000941           0.022738   \n",
       "2015-12-15 00:00:00+00:00            0.013516           0.044710   \n",
       "2015-12-16 00:00:00+00:00            0.000531          -0.003522   \n",
       "2015-12-17 00:00:00+00:00           -0.018147          -0.015037   \n",
       "2015-12-18 00:00:00+00:00           -0.012314          -0.008724   \n",
       "2015-12-21 00:00:00+00:00            0.016776          -0.000255   \n",
       "2015-12-22 00:00:00+00:00            0.002735           0.005054   \n",
       "2015-12-23 00:00:00+00:00            0.009501           0.032702   \n",
       "2015-12-24 00:00:00+00:00           -0.000620          -0.010724   \n",
       "2015-12-28 00:00:00+00:00           -0.001064          -0.007439   \n",
       "2015-12-29 00:00:00+00:00            0.007964           0.005336   \n",
       "2015-12-30 00:00:00+00:00           -0.007064          -0.013261   \n",
       "2015-12-31 00:00:00+00:00           -0.018175          -0.002050   \n",
       "2016-01-04 00:00:00+00:00           -0.024922          -0.006276   \n",
       "2016-01-05 00:00:00+00:00            0.014863           0.008511   \n",
       "\n",
       "                           Equity(484 [XRAY])  Equity(485 [XRX])  \\\n",
       "2011-01-07 00:00:00+00:00           -0.004044          -0.013953   \n",
       "2011-01-10 00:00:00+00:00            0.010466           0.009733   \n",
       "2011-01-11 00:00:00+00:00            0.007351           0.006116   \n",
       "2011-01-12 00:00:00+00:00            0.027182           0.004386   \n",
       "2011-01-13 00:00:00+00:00            0.000547          -0.018235   \n",
       "2011-01-14 00:00:00+00:00           -0.000287           0.026494   \n",
       "2011-01-18 00:00:00+00:00            0.011589           0.006044   \n",
       "2011-01-19 00:00:00+00:00           -0.019899          -0.012847   \n",
       "2011-01-20 00:00:00+00:00           -0.000841          -0.033798   \n",
       "2011-01-21 00:00:00+00:00           -0.003048          -0.000872   \n",
       "2011-01-24 00:00:00+00:00            0.001660           0.008049   \n",
       "2011-01-25 00:00:00+00:00            0.001134           0.015143   \n",
       "2011-01-26 00:00:00+00:00            0.000552          -0.076291   \n",
       "2011-01-27 00:00:00+00:00            0.016396           0.024664   \n",
       "2011-01-28 00:00:00+00:00           -0.021871          -0.022229   \n",
       "2011-01-31 00:00:00+00:00           -0.007560           0.006615   \n",
       "2011-02-01 00:00:00+00:00            0.024795           0.024498   \n",
       "2011-02-02 00:00:00+00:00           -0.010390          -0.001827   \n",
       "2011-02-03 00:00:00+00:00            0.008556           0.004596   \n",
       "2011-02-04 00:00:00+00:00            0.003048          -0.005506   \n",
       "2011-02-07 00:00:00+00:00            0.006852           0.002768   \n",
       "2011-02-08 00:00:00+00:00            0.005182          -0.002761   \n",
       "2011-02-09 00:00:00+00:00           -0.018441           0.003705   \n",
       "2011-02-10 00:00:00+00:00            0.005512          -0.004624   \n",
       "2011-02-11 00:00:00+00:00            0.007147           0.012021   \n",
       "2011-02-14 00:00:00+00:00           -0.005443           0.005476   \n",
       "2011-02-15 00:00:00+00:00            0.004097           0.003604   \n",
       "2011-02-16 00:00:00+00:00            0.000285           0.027093   \n",
       "2011-02-17 00:00:00+00:00           -0.001911           0.000000   \n",
       "2011-02-18 00:00:00+00:00            0.013148          -0.004390   \n",
       "...                                       ...                ...   \n",
       "2015-11-20 00:00:00+00:00            0.002793           0.002899   \n",
       "2015-11-23 00:00:00+00:00            0.007345           0.027692   \n",
       "2015-11-24 00:00:00+00:00           -0.009563          -0.012992   \n",
       "2015-11-25 00:00:00+00:00           -0.002792          -0.001913   \n",
       "2015-11-27 00:00:00+00:00            0.002633           0.003795   \n",
       "2015-11-30 00:00:00+00:00           -0.007363          -0.007524   \n",
       "2015-12-01 00:00:00+00:00            0.021600           0.013276   \n",
       "2015-12-02 00:00:00+00:00            0.007572          -0.029962   \n",
       "2015-12-03 00:00:00+00:00            0.002733          -0.000959   \n",
       "2015-12-04 00:00:00+00:00            0.007495           0.011599   \n",
       "2015-12-07 00:00:00+00:00           -0.001900          -0.029576   \n",
       "2015-12-08 00:00:00+00:00           -0.012067          -0.004930   \n",
       "2015-12-09 00:00:00+00:00           -0.021066          -0.009869   \n",
       "2015-12-10 00:00:00+00:00           -0.000317           0.014970   \n",
       "2015-12-11 00:00:00+00:00           -0.017755          -0.012793   \n",
       "2015-12-14 00:00:00+00:00           -0.001835          -0.017913   \n",
       "2015-12-15 00:00:00+00:00            0.004357           0.016222   \n",
       "2015-12-16 00:00:00+00:00            0.008507           0.024937   \n",
       "2015-12-17 00:00:00+00:00           -0.003142          -0.007787   \n",
       "2015-12-18 00:00:00+00:00           -0.010451          -0.003944   \n",
       "2015-12-21 00:00:00+00:00            0.007035           0.014779   \n",
       "2015-12-22 00:00:00+00:00            0.010047           0.038863   \n",
       "2015-12-23 00:00:00+00:00            0.007586           0.011193   \n",
       "2015-12-24 00:00:00+00:00           -0.002127           0.005553   \n",
       "2015-12-28 00:00:00+00:00            0.004930          -0.021138   \n",
       "2015-12-29 00:00:00+00:00            0.011436           0.011283   \n",
       "2015-12-30 00:00:00+00:00           -0.008079           0.001847   \n",
       "2015-12-31 00:00:00+00:00           -0.009119          -0.008371   \n",
       "2016-01-04 00:00:00+00:00           -0.032711          -0.031051   \n",
       "2016-01-05 00:00:00+00:00            0.020390          -0.001957   \n",
       "\n",
       "                           Equity(486 [XYL])  Equity(487 [YUM])  \\\n",
       "2011-01-07 00:00:00+00:00           0.000000           0.012457   \n",
       "2011-01-10 00:00:00+00:00           0.000000           0.001440   \n",
       "2011-01-11 00:00:00+00:00           0.000000          -0.006470   \n",
       "2011-01-12 00:00:00+00:00           0.000000           0.002631   \n",
       "2011-01-13 00:00:00+00:00           0.000000          -0.005084   \n",
       "2011-01-14 00:00:00+00:00           0.000000          -0.021661   \n",
       "2011-01-18 00:00:00+00:00           0.000000           0.029453   \n",
       "2011-01-19 00:00:00+00:00           0.000000           0.000818   \n",
       "2011-01-20 00:00:00+00:00           0.000000          -0.013182   \n",
       "2011-01-21 00:00:00+00:00           0.000000          -0.007590   \n",
       "2011-01-24 00:00:00+00:00           0.000000           0.000601   \n",
       "2011-01-25 00:00:00+00:00           0.000000          -0.006208   \n",
       "2011-01-26 00:00:00+00:00           0.000000          -0.004803   \n",
       "2011-01-27 00:00:00+00:00           0.000000          -0.003746   \n",
       "2011-01-28 00:00:00+00:00           0.000000          -0.025001   \n",
       "2011-01-31 00:00:00+00:00           0.000000           0.007748   \n",
       "2011-02-01 00:00:00+00:00           0.000000           0.014102   \n",
       "2011-02-02 00:00:00+00:00           0.000000           0.006562   \n",
       "2011-02-03 00:00:00+00:00           0.000000           0.031413   \n",
       "2011-02-04 00:00:00+00:00           0.000000           0.001408   \n",
       "2011-02-07 00:00:00+00:00           0.000000           0.002028   \n",
       "2011-02-08 00:00:00+00:00           0.000000           0.003851   \n",
       "2011-02-09 00:00:00+00:00           0.000000          -0.001821   \n",
       "2011-02-10 00:00:00+00:00           0.000000           0.004853   \n",
       "2011-02-11 00:00:00+00:00           0.000000           0.000616   \n",
       "2011-02-14 00:00:00+00:00           0.000000           0.010657   \n",
       "2011-02-15 00:00:00+00:00           0.000000           0.008526   \n",
       "2011-02-16 00:00:00+00:00           0.000000           0.008898   \n",
       "2011-02-17 00:00:00+00:00           0.000000           0.003906   \n",
       "2011-02-18 00:00:00+00:00           0.000000          -0.004110   \n",
       "...                                      ...                ...   \n",
       "2015-11-20 00:00:00+00:00          -0.004498           0.015060   \n",
       "2015-11-23 00:00:00+00:00           0.001322          -0.000966   \n",
       "2015-11-24 00:00:00+00:00          -0.001871          -0.004252   \n",
       "2015-11-25 00:00:00+00:00           0.004824           0.002894   \n",
       "2015-11-27 00:00:00+00:00          -0.002140           0.005105   \n",
       "2015-11-30 00:00:00+00:00          -0.006928          -0.006183   \n",
       "2015-12-01 00:00:00+00:00           0.008582           0.027170   \n",
       "2015-12-02 00:00:00+00:00          -0.018335           0.006313   \n",
       "2015-12-03 00:00:00+00:00          -0.005676          -0.024272   \n",
       "2015-12-04 00:00:00+00:00           0.024774           0.041159   \n",
       "2015-12-07 00:00:00+00:00          -0.019647           0.003540   \n",
       "2015-12-08 00:00:00+00:00          -0.017074          -0.010735   \n",
       "2015-12-09 00:00:00+00:00          -0.000570          -0.023679   \n",
       "2015-12-10 00:00:00+00:00           0.012138          -0.008256   \n",
       "2015-12-11 00:00:00+00:00          -0.013062          -0.025836   \n",
       "2015-12-14 00:00:00+00:00           0.011580           0.004910   \n",
       "2015-12-15 00:00:00+00:00           0.001635           0.013410   \n",
       "2015-12-16 00:00:00+00:00           0.020719           0.012809   \n",
       "2015-12-17 00:00:00+00:00          -0.026697          -0.018224   \n",
       "2015-12-18 00:00:00+00:00          -0.017002          -0.004991   \n",
       "2015-12-21 00:00:00+00:00           0.008360           0.021714   \n",
       "2015-12-22 00:00:00+00:00           0.009977          -0.005448   \n",
       "2015-12-23 00:00:00+00:00           0.017237           0.015349   \n",
       "2015-12-24 00:00:00+00:00          -0.001614          -0.001620   \n",
       "2015-12-28 00:00:00+00:00          -0.003484          -0.002177   \n",
       "2015-12-29 00:00:00+00:00           0.004307           0.005415   \n",
       "2015-12-30 00:00:00+00:00          -0.006182          -0.005781   \n",
       "2015-12-31 00:00:00+00:00          -0.010031          -0.010299   \n",
       "2016-01-04 00:00:00+00:00          -0.011520          -0.011489   \n",
       "2016-01-05 00:00:00+00:00          -0.000286          -0.002495   \n",
       "\n",
       "                           Equity(488 [ZBH])  Equity(489 [ZION])  \\\n",
       "2011-01-07 00:00:00+00:00          -0.000181           -0.010458   \n",
       "2011-01-10 00:00:00+00:00           0.007784           -0.017945   \n",
       "2011-01-11 00:00:00+00:00           0.035676            0.007467   \n",
       "2011-01-12 00:00:00+00:00           0.014741           -0.011903   \n",
       "2011-01-13 00:00:00+00:00          -0.004665           -0.009178   \n",
       "2011-01-14 00:00:00+00:00           0.005949            0.033177   \n",
       "2011-01-18 00:00:00+00:00           0.006998           -0.008534   \n",
       "2011-01-19 00:00:00+00:00          -0.004098           -0.018433   \n",
       "2011-01-20 00:00:00+00:00          -0.001612           -0.007972   \n",
       "2011-01-21 00:00:00+00:00           0.009325            0.024020   \n",
       "2011-01-24 00:00:00+00:00          -0.016501           -0.023021   \n",
       "2011-01-25 00:00:00+00:00           0.017142           -0.008836   \n",
       "2011-01-26 00:00:00+00:00          -0.019524           -0.010626   \n",
       "2011-01-27 00:00:00+00:00           0.068754            0.020160   \n",
       "2011-01-28 00:00:00+00:00          -0.008472           -0.013873   \n",
       "2011-01-31 00:00:00+00:00           0.009902            0.006378   \n",
       "2011-02-01 00:00:00+00:00           0.017746            0.030970   \n",
       "2011-02-02 00:00:00+00:00           0.005161           -0.003706   \n",
       "2011-02-03 00:00:00+00:00          -0.000333           -0.000394   \n",
       "2011-02-04 00:00:00+00:00           0.002471            0.016111   \n",
       "2011-02-07 00:00:00+00:00          -0.010876            0.027617   \n",
       "2011-02-08 00:00:00+00:00          -0.000495            0.004780   \n",
       "2011-02-09 00:00:00+00:00          -0.009851           -0.004757   \n",
       "2011-02-10 00:00:00+00:00           0.011449           -0.026498   \n",
       "2011-02-11 00:00:00+00:00           0.009660            0.014256   \n",
       "2011-02-14 00:00:00+00:00           0.002484           -0.010021   \n",
       "2011-02-15 00:00:00+00:00          -0.001815           -0.004461   \n",
       "2011-02-16 00:00:00+00:00           0.010557            0.001206   \n",
       "2011-02-17 00:00:00+00:00           0.015325           -0.003227   \n",
       "2011-02-18 00:00:00+00:00           0.023782           -0.017960   \n",
       "...                                      ...                 ...   \n",
       "2015-11-20 00:00:00+00:00          -0.003176            0.000000   \n",
       "2015-11-23 00:00:00+00:00          -0.008581           -0.001992   \n",
       "2015-11-24 00:00:00+00:00          -0.009043            0.002650   \n",
       "2015-11-25 00:00:00+00:00          -0.006174           -0.000309   \n",
       "2015-11-27 00:00:00+00:00          -0.002869            0.005013   \n",
       "2015-11-30 00:00:00+00:00           0.000101           -0.004339   \n",
       "2015-12-01 00:00:00+00:00           0.016927            0.015028   \n",
       "2015-12-02 00:00:00+00:00          -0.004473           -0.015448   \n",
       "2015-12-03 00:00:00+00:00          -0.028367           -0.015725   \n",
       "2015-12-04 00:00:00+00:00           0.011977            0.024452   \n",
       "2015-12-07 00:00:00+00:00          -0.001384           -0.042085   \n",
       "2015-12-08 00:00:00+00:00          -0.006277           -0.031813   \n",
       "2015-12-09 00:00:00+00:00           0.002205           -0.007490   \n",
       "2015-12-10 00:00:00+00:00          -0.000297            0.014759   \n",
       "2015-12-11 00:00:00+00:00          -0.010112           -0.029782   \n",
       "2015-12-14 00:00:00+00:00           0.005356           -0.014991   \n",
       "2015-12-15 00:00:00+00:00           0.015787            0.035626   \n",
       "2015-12-16 00:00:00+00:00           0.008606            0.010755   \n",
       "2015-12-17 00:00:00+00:00          -0.011966           -0.015960   \n",
       "2015-12-18 00:00:00+00:00          -0.017384           -0.037845   \n",
       "2015-12-21 00:00:00+00:00           0.012842            0.002271   \n",
       "2015-12-22 00:00:00+00:00           0.014966            0.014553   \n",
       "2015-12-23 00:00:00+00:00           0.010219            0.018773   \n",
       "2015-12-24 00:00:00+00:00           0.001364            0.003975   \n",
       "2015-12-28 00:00:00+00:00          -0.006413           -0.005033   \n",
       "2015-12-29 00:00:00+00:00           0.007235            0.006174   \n",
       "2015-12-30 00:00:00+00:00          -0.002921           -0.012235   \n",
       "2015-12-31 00:00:00+00:00           0.001176           -0.006212   \n",
       "2016-01-04 00:00:00+00:00          -0.007604           -0.021614   \n",
       "2016-01-05 00:00:00+00:00           0.020820           -0.010853   \n",
       "\n",
       "                           Equity(490 [ZTS])  \n",
       "2011-01-07 00:00:00+00:00           0.000000  \n",
       "2011-01-10 00:00:00+00:00           0.000000  \n",
       "2011-01-11 00:00:00+00:00           0.000000  \n",
       "2011-01-12 00:00:00+00:00           0.000000  \n",
       "2011-01-13 00:00:00+00:00           0.000000  \n",
       "2011-01-14 00:00:00+00:00           0.000000  \n",
       "2011-01-18 00:00:00+00:00           0.000000  \n",
       "2011-01-19 00:00:00+00:00           0.000000  \n",
       "2011-01-20 00:00:00+00:00           0.000000  \n",
       "2011-01-21 00:00:00+00:00           0.000000  \n",
       "2011-01-24 00:00:00+00:00           0.000000  \n",
       "2011-01-25 00:00:00+00:00           0.000000  \n",
       "2011-01-26 00:00:00+00:00           0.000000  \n",
       "2011-01-27 00:00:00+00:00           0.000000  \n",
       "2011-01-28 00:00:00+00:00           0.000000  \n",
       "2011-01-31 00:00:00+00:00           0.000000  \n",
       "2011-02-01 00:00:00+00:00           0.000000  \n",
       "2011-02-02 00:00:00+00:00           0.000000  \n",
       "2011-02-03 00:00:00+00:00           0.000000  \n",
       "2011-02-04 00:00:00+00:00           0.000000  \n",
       "2011-02-07 00:00:00+00:00           0.000000  \n",
       "2011-02-08 00:00:00+00:00           0.000000  \n",
       "2011-02-09 00:00:00+00:00           0.000000  \n",
       "2011-02-10 00:00:00+00:00           0.000000  \n",
       "2011-02-11 00:00:00+00:00           0.000000  \n",
       "2011-02-14 00:00:00+00:00           0.000000  \n",
       "2011-02-15 00:00:00+00:00           0.000000  \n",
       "2011-02-16 00:00:00+00:00           0.000000  \n",
       "2011-02-17 00:00:00+00:00           0.000000  \n",
       "2011-02-18 00:00:00+00:00           0.000000  \n",
       "...                                      ...  \n",
       "2015-11-20 00:00:00+00:00           0.008950  \n",
       "2015-11-23 00:00:00+00:00          -0.007600  \n",
       "2015-11-24 00:00:00+00:00          -0.000651  \n",
       "2015-11-25 00:00:00+00:00           0.000868  \n",
       "2015-11-27 00:00:00+00:00           0.002343  \n",
       "2015-11-30 00:00:00+00:00          -0.008071  \n",
       "2015-12-01 00:00:00+00:00           0.006632  \n",
       "2015-12-02 00:00:00+00:00          -0.013610  \n",
       "2015-12-03 00:00:00+00:00          -0.025244  \n",
       "2015-12-04 00:00:00+00:00           0.027882  \n",
       "2015-12-07 00:00:00+00:00          -0.011841  \n",
       "2015-12-08 00:00:00+00:00           0.000666  \n",
       "2015-12-09 00:00:00+00:00          -0.015900  \n",
       "2015-12-10 00:00:00+00:00           0.019695  \n",
       "2015-12-11 00:00:00+00:00          -0.005856  \n",
       "2015-12-14 00:00:00+00:00           0.016583  \n",
       "2015-12-15 00:00:00+00:00           0.008156  \n",
       "2015-12-16 00:00:00+00:00           0.002538  \n",
       "2015-12-17 00:00:00+00:00          -0.007637  \n",
       "2015-12-18 00:00:00+00:00          -0.002791  \n",
       "2015-12-21 00:00:00+00:00           0.015894  \n",
       "2015-12-22 00:00:00+00:00           0.008027  \n",
       "2015-12-23 00:00:00+00:00           0.005444  \n",
       "2015-12-24 00:00:00+00:00           0.003121  \n",
       "2015-12-28 00:00:00+00:00          -0.004784  \n",
       "2015-12-29 00:00:00+00:00           0.008997  \n",
       "2015-12-30 00:00:00+00:00          -0.001454  \n",
       "2015-12-31 00:00:00+00:00          -0.007051  \n",
       "2016-01-04 00:00:00+00:00          -0.013564  \n",
       "2016-01-05 00:00:00+00:00           0.015647  \n",
       "\n",
       "[1256 rows x 490 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "returns_df = \\\n",
    "    get_pricing(\n",
    "        data_portal,\n",
    "        trading_calendar,\n",
    "        universe_tickers,\n",
    "        universe_end_date - pd.DateOffset(years=5),\n",
    "        universe_end_date)\\\n",
    "    .pct_change()[1:].fillna(0) #convert prices into returns\n",
    "\n",
    "returns_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Let's look at a two stock portfolio\n",
    "\n",
    "Let's pretend we have a portfolio of two stocks.  We'll pick Apple and Microsoft in this example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>asset_return_aapl</th>\n",
       "      <th>asset_return_msft</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-07 00:00:00+00:00</th>\n",
       "      <td>0.007146</td>\n",
       "      <td>-0.007597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-10 00:00:00+00:00</th>\n",
       "      <td>0.018852</td>\n",
       "      <td>-0.013311</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           asset_return_aapl  asset_return_msft\n",
       "2011-01-07 00:00:00+00:00           0.007146          -0.007597\n",
       "2011-01-10 00:00:00+00:00           0.018852          -0.013311"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aapl_col = returns_df.columns[3]\n",
    "msft_col = returns_df.columns[312]\n",
    "asset_return_1 = returns_df[aapl_col].rename('asset_return_aapl')\n",
    "asset_return_2 = returns_df[msft_col].rename('asset_return_msft')\n",
    "asset_return_df = pd.concat([asset_return_1,asset_return_2],axis=1)\n",
    "asset_return_df.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Factor returns\n",
    "Let's make up a \"factor\" by taking an average of all stocks in our list.  You can think of this as an equal weighted index of the 490 stocks, kind of like a measure of the \"market\".  We'll also make another factor by calculating the median of all the stocks.  These are mainly intended to help us generate some data to work with.  We'll go into how some common risk factors are generated later in the lessons.\n",
    "\n",
    "Also note that we're setting axis=1 so that we calculate a value for each time period (row) instead of one value for each column (assets)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "factor_return_1 = returns_df.mean(axis=1)\n",
    "factor_return_2 = returns_df.median(axis=1)\n",
    "factor_return_l = [factor_return_1, factor_return_2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Factor exposures\n",
    "\n",
    "Factor exposures refer to how \"exposed\" a stock is to each factor.  We'll get into this more later.  For now, just think of this as one number for each stock, for each of the factors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "For now, just assume that we're calculating a number for each \n",
    "stock, for each factor, which represents how \"exposed\" each stock is\n",
    "to each factor. \n",
    "We'll discuss how factor exposure is calculated later in the lessons.\n",
    "\"\"\"\n",
    "def get_factor_exposures(factor_return_l, asset_return):\n",
    "    lr = LinearRegression()\n",
    "    X = np.array(factor_return_l).T\n",
    "    y = np.array(asset_return.values)\n",
    "    lr.fit(X,y)\n",
    "    return lr.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "factor_exposure_l = []\n",
    "for i in range(len(asset_return_df.columns)):\n",
    "    factor_exposure_l.append(\n",
    "        get_factor_exposures(factor_return_l,\n",
    "                             asset_return_df[asset_return_df.columns[i]]\n",
    "                            ))\n",
    "    \n",
    "factor_exposure_a = np.array(factor_exposure_l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "factor_exposures for asset 1 [ 1.35101534 -0.58353198]\n",
      "factor_exposures for asset 2 [-0.2283345   1.16364007]\n"
     ]
    }
   ],
   "source": [
    "print(f\"factor_exposures for asset 1 {factor_exposure_a[0]}\")\n",
    "print(f\"factor_exposures for asset 2 {factor_exposure_a[1]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 1 Portfolio's factor exposures\n",
    "\n",
    "Let's make up some portfolio weights for now; in a later lesson, we'll look at how portfolio optimization combines alpha factors and a risk factor model to choose asset weights.\n",
    "\n",
    "$\\beta_{p,k} = \\sum_{i=1}^{N}(x_i \\times \\beta_{i,k})$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "weight_1 = 0.60 #let's give AAPL a portfolio weight\n",
    "weight_2 = 0.40 #give MSFT a portfolio weight\n",
    "weight_a = np.array([weight_1, weight_2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the sake of understanding, try saving each of the values\n",
    "into a separate variable to perform the multipliations and additions\n",
    "Check that your calculations for portfolio factor exposure match\n",
    "the output of this dot product:\n",
    "```\n",
    "weight_a.dot(factor_exposure_a)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7192754067760122"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TODO: calculate portfolio's exposure to factor 1\n",
    "factor_exposure_1_1 = factor_exposure_a[0,0]\n",
    "factor_exposure_2_1 = factor_exposure_a[1,0]\n",
    "factor_exposure_p_1 = weight_1 * factor_exposure_1_1 + \\\n",
    "                        weight_2 * factor_exposure_2_1\n",
    "factor_exposure_p_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.11533683816249468"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TODO: calculate portfolio's exposure to factor 2\n",
    "factor_exposure_1_2 = factor_exposure_a[0,1]\n",
    "factor_exposure_2_2 = factor_exposure_a[1,1]\n",
    "factor_exposure_p_2 = weight_1 * factor_exposure_1_2 + \\\n",
    "                        weight_2 * factor_exposure_2_2\n",
    "factor_exposure_p_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 2 Calculate portfolio return\n",
    "\n",
    "For clarity, try storing the pieces into their own \n",
    "named variables and writing out the multiplications and addition.\n",
    "\n",
    "You can check if your answer matches this output:\n",
    "```\n",
    "asset_return_df.values.dot(weight_a)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2011-01-07 00:00:00+00:00    0.001249\n",
       "2011-01-10 00:00:00+00:00    0.005987\n",
       "Freq: C, Name: portfolio_return, dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TODO calculate the portfolio return\n",
    "asset_return_1 = asset_return_df.values[:,0]\n",
    "asset_return_2 = asset_return_df.values[:,1]\n",
    "portfolio_return = (weight_a[0] * asset_return_1) + \\\n",
    "                    (weight_a[1] * asset_return_2)\n",
    "\n",
    "portfolio_return = pd.Series(portfolio_return,index=asset_return_df.index).rename('portfolio_return')\n",
    "portfolio_return.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 3 Contribution of Factors\n",
    "\n",
    "The sum of the products of factor exposure times factor return is the contribution of the factors.  It's also called the \"common return.\" calculate the common return of the portfolio, given the two factor exposures and the two factor returns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2011-01-07 00:00:00+00:00    0.000051\n",
       "2011-01-10 00:00:00+00:00    0.000269\n",
       "Freq: C, Name: common_return, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TODO Calculate the contribution of the two factors to the return of this example asset\n",
    "common_return = (factor_exposure_p_1 * factor_return_1) + (factor_exposure_p_2 * factor_return_2)\n",
    "common_return = common_return.rename('common_return')\n",
    "\n",
    "common_return.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz 4 Specific Return\n",
    "The specific return is the part of the portfolio return that isn't explained by the factors.  So it's the actual return minus the common return.  \n",
    "Calculate the specific return of the stock."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: calculate the specific return of this asset\n",
    "specific_return = portfolio_return - common_return\n",
    "specific_return = specific_return.rename('specific_return')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize the common return and specific return\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>common_return</th>\n",
       "      <th>specific_return</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-07 00:00:00+00:00</th>\n",
       "      <td>0.000051</td>\n",
       "      <td>0.001198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-10 00:00:00+00:00</th>\n",
       "      <td>0.000269</td>\n",
       "      <td>0.005717</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           common_return  specific_return\n",
       "2011-01-07 00:00:00+00:00       0.000051         0.001198\n",
       "2011-01-10 00:00:00+00:00       0.000269         0.005717"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "return_components = pd.concat([common_return,specific_return],axis=1)\n",
    "return_components.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1b20029e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1b166c3940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "return_components.plot(title=\"asset return = common return + specific return\");\n",
    "pd.DataFrame(portfolio_return).plot(color='purple');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
